Merge branch 'master' into xsn/fix_lora

2024-12-26 03:14:35 +00:00 · 2024-07-10 19:52:39 +02:00 · 2024-07-10 19:52:39 +02:00 · e68344cb06
commit e68344cb06
parent 1faf7e5be6 dd07a123b7
79 changed files with 3369 additions and 411 deletions
--- a/.devops/nix/package.nix
+++ b/.devops/nix/package.nix
@ -89,6 +89,22 @@ let
      ps.tiktoken
      ps.torchWithoutCuda
      ps.transformers
+
+      # server bench
+      ps.matplotlib
+
+      # server tests
+      ps.openai
+      ps.behave
+      ps.prometheus-client
+
+      # for examples/pydantic-models-to-grammar-examples.py
+      ps.docstring-parser
+      ps.pydantic
+
+      # for scripts/compare-llama-bench.py
+      ps.gitpython
+      ps.tabulate
    ]
  );

--- a/.github/labeler.yml
+++ b/.github/labeler.yml
@ -16,7 +16,9 @@ SYCL:
        - any-glob-to-any-file:
            - ggml/include/ggml-sycl.h
            - ggml/src/ggml-sycl.cpp
-            - README-sycl.md
+            - ggml/src/ggml-sycl/**
+            - docs/backend/SYCL.md
+            - examples/sycl/**
 Nvidia GPU:
    - changed-files:
        - any-glob-to-any-file:
--- a/.github/workflows/python-type-check.yml
+++ b/.github/workflows/python-type-check.yml
@ -0,0 +1,38 @@
+name: Python Type-Check
+
+on:
+  push:
+    paths:
+      - '.github/workflows/python-type-check.yml'
+      - '**.py'
+      - '**/requirements*.txt'
+  pull_request:
+    paths:
+      - '.github/workflows/python-type-check.yml'
+      - '**.py'
+      - '**/requirements*.txt'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  python-type-check:
+    runs-on: ubuntu-latest
+    name: pyright type-check
+    steps:
+      - name: Check out source repository
+        uses: actions/checkout@v4
+      - name: Set up Python environment
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+      - name: Install Python dependencies
+        # TODO: use a venv
+        run: pip install -r requirements/requirements-all.txt
+      - name: Type-check with Pyright
+        uses: jakebailey/pyright-action@v2
+        with:
+          version: 1.1.370
+          level: warning
+          warnings: true
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@ -50,9 +50,6 @@ endif()
 # option list
 #

-# general
-option(LLAMA_CCACHE "llama: use ccache if available" ON)
-
 # debug
 option(LLAMA_ALL_WARNINGS           "llama: enable all compiler warnings"                   ON)
 option(LLAMA_ALL_WARNINGS_3RD_PARTY "llama: enable all compiler warnings in 3rd party libs" OFF)
@ -77,7 +74,6 @@ option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF)
 include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)

 # override ggml options
-set(GGML_CCACHE             ${LLAMA_CCACHE})
 set(GGML_SANITIZE_THREAD    ${LLAMA_SANITIZE_THREAD})
 set(GGML_SANITIZE_ADDRESS   ${LLAMA_SANITIZE_ADDRESS})
 set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED})
@ -115,7 +111,10 @@ llama_option_depr(WARNING     LLAMA_SYCL_F16            GGML_SYCL_F16)
 # build the library
 #

-add_subdirectory(ggml)
+if (NOT TARGET ggml)
+    add_subdirectory(ggml)
+    # ... otherwise assume ggml is added by a parent CMakeLists.txt
+endif()
 add_subdirectory(src)

 #
--- a/100
+++ b/100
@ -64,10 +64,14 @@ TEST_TARGETS = \
 	tests/test-tokenizer-1-spm

 # Legacy build targets that were renamed in #7809, but should still be removed when the project is cleaned
-LEGACY_TARGETS = main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
+LEGACY_TARGETS_CLEAN = main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
 	simple batched batched-bench save-load-state server gguf gguf-split eval-callback llama-bench libllava.a llava-cli baby-llama \
 	retrieval speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey gritlm

+# Legacy build targets that were renamed in #7809, but we want to build binaries that for them that output a deprecation warning if people try to use them.
+#  We don't want to clutter things too much, so we only build replacements for the most commonly used binaries.
+LEGACY_TARGETS_BUILD = main quantize perplexity embedding server finetune
+
 # Deprecation aliases
 ifdef LLAMA_CUBLAS
 $(error LLAMA_CUBLAS is removed. Use GGML_CUDA instead.)
@ -193,7 +197,7 @@ ifdef GGML_RPC
 	BUILD_TARGETS += rpc-server
 endif

-default: $(BUILD_TARGETS)
+default: $(BUILD_TARGETS) $(LEGACY_TARGETS_BUILD)

 test: $(TEST_TARGETS)
 	@failures=0; \
@ -228,7 +232,7 @@ test: $(TEST_TARGETS)
 	fi
 	@echo 'All tests passed.'

-all: $(BUILD_TARGETS) $(TEST_TARGETS)
+all: $(BUILD_TARGETS) $(TEST_TARGETS) $(LEGACY_TARGETS_BUILD)

 ifdef RISCV_CROSS_COMPILE
 CC	:= riscv64-unknown-linux-gnu-gcc
@ -245,17 +249,22 @@ MK_CFLAGS    = -std=c11   -fPIC
 MK_CXXFLAGS  = -std=c++11 -fPIC
 MK_NVCCFLAGS = -std=c++11

-ifndef LLAMA_NO_CCACHE
+ifdef LLAMA_NO_CCACHE
+GGML_NO_CCACHE := 1
+DEPRECATE_WARNING := 1
+endif
+
+ifndef GGML_NO_CCACHE
 CCACHE := $(shell which ccache)
 ifdef CCACHE
 export CCACHE_SLOPPINESS = time_macros
-$(info I ccache found, compilation results will be cached. Disable with LLAMA_NO_CCACHE.)
+$(info I ccache found, compilation results will be cached. Disable with GGML_NO_CCACHE.)
 CC    := $(CCACHE) $(CC)
 CXX   := $(CCACHE) $(CXX)
 else
 $(info I ccache not found. Consider installing it for faster compilation.)
 endif # CCACHE
-endif # LLAMA_NO_CCACHE
+endif # GGML_NO_CCACHE

 # clock_gettime came in POSIX.1b (1993)
 # CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional
@ -545,7 +554,7 @@ endif # GGML_BLIS

 ifndef GGML_NO_LLAMAFILE
 	MK_CPPFLAGS += -DGGML_USE_LLAMAFILE
-	OBJ_GGML    += ggml/src/sgemm.o
+	OBJ_GGML    += ggml/src/llamafile/sgemm.o
 endif

 ifdef GGML_RPC
@ -826,7 +835,8 @@ OBJ_GGML += \
 	ggml/src/ggml.o \
 	ggml/src/ggml-alloc.o \
 	ggml/src/ggml-backend.o \
-	ggml/src/ggml-quants.o
+	ggml/src/ggml-quants.o \
+	ggml/src/ggml-aarch64.o

 OBJ_LLAMA = \
 	src/llama.o \
@ -926,6 +936,7 @@ $(info   - LLAMA_NO_LLAMAFILE)
 $(info   - LLAMA_NO_ACCELERATE)
 $(info   - LLAMA_NO_OPENMP)
 $(info   - LLAMA_NO_METAL)
+$(info   - LLAMA_NO_CCACHE)
 $(info )
 endif

@ -959,15 +970,22 @@ ggml/src/ggml-quants.o: \
 	ggml/src/ggml-common.h
 	$(CC) $(CFLAGS)    -c $< -o $@

+ggml/src/ggml-aarch64.o: \
+	ggml/src/ggml-aarch64.c \
+	ggml/include/ggml.h \
+	ggml/src/ggml-aarch64.h \
+	ggml/src/ggml-common.h
+	$(CC) $(CFLAGS)    -c $< -o $@
+
 ggml/src/ggml-blas.o: \
 	ggml/src/ggml-blas.cpp \
 	ggml/include/ggml-blas.h
 	$(CXX) $(CXXFLAGS) -c $< -o $@

 ifndef GGML_NO_LLAMAFILE
-ggml/src/sgemm.o: \
-	ggml/src/sgemm.cpp \
-	ggml/src/sgemm.h \
+ggml/src/llamafile/sgemm.o: \
+	ggml/src/llamafile/sgemm.cpp \
+	ggml/src/llamafile/sgemm.h \
 	ggml/include/ggml.h
 	$(CXX) $(CXXFLAGS) -c $< -o $@
 endif # GGML_NO_LLAMAFILE
@ -1092,7 +1110,7 @@ clean:
 	rm -vrf ggml/src/ggml-cuda/template-instances/*.o
 	rm -rvf $(BUILD_TARGETS)
 	rm -rvf $(TEST_TARGETS)
-	rm -rvf $(LEGACY_TARGETS)
+	rm -rvf $(LEGACY_TARGETS_CLEAN)
 	find examples pocs -type f -name "*.o" -delete

 #
@ -1488,3 +1506,61 @@ llama-q8dot: pocs/vdot/q8dot.cpp ggml/src/ggml.o \
 	$(OBJ_GGML)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+
+#
+# Deprecated binaries that we want to keep around long enough for people to migrate to the new filenames, then these can be removed.
+#
+# Mark legacy binary targets as .PHONY so that they are always checked.
+.PHONY: main quantize perplexity embedding server finetune
+
+# NOTE: We currently will always build the deprecation-warning `main` and `server` binaries to help users migrate.
+#  Eventually we will want to remove these target from building all the time.
+main: examples/deprecation-warning/deprecation-warning.cpp
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "NOTICE: The 'main' binary is deprecated. Please use 'llama-cli' instead."
+
+server: examples/deprecation-warning/deprecation-warning.cpp
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "NOTICE: The 'server' binary is deprecated. Please use 'llama-server' instead."
+
+quantize: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard quantize))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'quantize' binary is deprecated. Please use 'llama-quantize' instead."
+	@echo "  Remove the 'quantize' binary to remove this warning."
+	@echo "#########"
+endif
+
+perplexity: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard perplexity))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'perplexity' binary is deprecated. Please use 'llama-perplexity' instead."
+	@echo "  Remove the 'perplexity' binary to remove this warning."
+	@echo "#########"
+endif
+
+embedding: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard embedding))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'embedding' binary is deprecated. Please use 'llama-embedding' instead."
+	@echo "  Remove the 'embedding' binary to remove this warning."
+	@echo "#########"
+endif
+
+finetune: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard finetune))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'finetune' binary is deprecated. Please use 'llama-finetune' instead."
+	@echo "  Remove the 'finetune' binary to remove this warning."
+	@echo "#########"
+endif
--- a/Package.swift
+++ b/Package.swift
@ -10,6 +10,7 @@ var sources = [
    "ggml/src/ggml-alloc.c",
    "ggml/src/ggml-backend.c",
    "ggml/src/ggml-quants.c",
+    "ggml/src/ggml-aarch64.c",
 ]

 var resources: [Resource] = []
--- a/README.md
+++ b/README.md
@ -96,8 +96,9 @@ Typically finetunes of the base models below are supported as well.
 - [x] [GritLM-7B](https://huggingface.co/GritLM/GritLM-7B) + [GritLM-8x7B](https://huggingface.co/GritLM/GritLM-8x7B)
 - [x] [OLMo](https://allenai.org/olmo)
 - [x] [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) + [Pythia](https://github.com/EleutherAI/pythia)
+- [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b)

-(instructions for supporting more models: [HOWTO-add-model.md](./docs/HOWTO-add-model.md))
+(instructions for supporting more models: [HOWTO-add-model.md](./docs/development/HOWTO-add-model.md))

 **Multimodal models:**

@ -452,7 +453,7 @@ To learn more how to measure perplexity using llama.cpp, [read this documentatio
 - [How to build](./docs/build.md)
 - [Running on Docker](./docs/docker.md)
 - [Build on Android](./docs/android.md)
- [Performance troubleshooting](./docs/token_generation_performance_tips.md)
+- [Performance troubleshooting](./docs/development/token_generation_performance_tips.md)
 - [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks)

 **Seminal papers and background on the models**
--- a/common/common.cpp
+++ b/common/common.cpp
@ -1,3 +1,7 @@
+#if defined(_MSC_VER)
+#define _SILENCE_CXX17_CODECVT_HEADER_DEPRECATION_WARNING
+#endif
+
 #include "common.h"
 // Change JSON_ASSERT from assert() to GGML_ASSERT:
 #define JSON_ASSERT GGML_ASSERT
--- a/common/log.h
+++ b/common/log.h
@ -630,7 +630,7 @@ inline std::string LOG_TOKENS_TOSTR_PRETTY(const C & ctx, const T & tokens)
    buf << "[ ";

    bool first = true;
-    for (const auto &token : tokens)
+    for (const auto & token : tokens)
    {
        if (!first) {
            buf << ", ";
--- a/common/sampling.cpp
+++ b/common/sampling.cpp
@ -282,8 +282,6 @@ static llama_token llama_sampling_sample_impl(
        GGML_ASSERT(!original_logits.empty());
    }
    llama_token id = 0;
-    // Get a pointer to the logits
-    float * logits = llama_get_logits_ith(ctx_main, idx);

    if (temp < 0.0) {
        // greedy sampling, with probs
@ -324,6 +322,9 @@ static llama_token llama_sampling_sample_impl(
    }

    if (ctx_sampling->grammar != NULL && !is_resampling) {
+        // Get a pointer to the logits
+        float * logits = llama_get_logits_ith(ctx_main, idx);
+
        // Create an array with a single token data element for the sampled id
        llama_token_data single_token_data = {id, logits[id], 0.0f};
        llama_token_data_array single_token_data_array = { &single_token_data, 1, false };
@ -377,7 +378,7 @@ static llama_token_data_array llama_sampling_prepare_impl(
    if (ctx_sampling->grammar != NULL && !apply_grammar) {
        GGML_ASSERT(original_logits != NULL);
        // Only make a copy of the original logits if we are not applying grammar checks, not sure if I actually have to do this.
-        *original_logits = {logits, logits + llama_n_vocab(llama_get_model(ctx_main))};
+        *original_logits = {logits, logits + n_vocab};
    }

    // apply params.logit_bias map
@ -390,10 +391,10 @@ static llama_token_data_array llama_sampling_prepare_impl(
        llama_sample_apply_guidance(ctx_main, logits, logits_guidance, params.cfg_scale);
    }

-    cur.clear();
+    cur.resize(n_vocab);

    for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
-        cur.emplace_back(llama_token_data{token_id, logits[token_id], 0.0f});
+        cur[token_id] = llama_token_data{token_id, logits[token_id], 0.0f};
    }

    llama_token_data_array cur_p = { cur.data(), cur.size(), false };
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@ -265,7 +265,7 @@ class Model:
                    break

            for new_name, data in ((n, d.squeeze().numpy()) for n, d in self.modify_tensors(data_torch, name, bid)):
-                data: np.ndarray = data  # type hint
+                data: np.ndarray  # type hint
                n_dims = len(data.shape)
                data_dtype = data.dtype
                data_qtype: gguf.GGMLQuantizationType | None = None
@ -602,10 +602,6 @@ class Model:

        tokenizer_path = self.dir_model / 'tokenizer.model'

-        tokens: list[bytes] = []
-        scores: list[float] = []
-        toktypes: list[int] = []
-
        if not tokenizer_path.is_file():
            raise FileNotFoundError(f"File not found: {tokenizer_path}")

@ -1363,7 +1359,7 @@ class LlamaModel(Model):

    def set_vocab(self):
        try:
-            self. _set_vocab_sentencepiece()
+            self._set_vocab_sentencepiece()
        except FileNotFoundError:
            try:
                self._set_vocab_llama_hf()
@ -2127,7 +2123,7 @@ class InternLM2Model(Model):
            logger.error(f'Error: Missing {tokenizer_path}')
            sys.exit(1)

-        sentencepiece_model = model.ModelProto()
+        sentencepiece_model = model.ModelProto()  # pyright: ignore[reportAttributeAccessIssue]
        sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read())
        add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix

@ -2155,6 +2151,9 @@ class InternLM2Model(Model):
                toktype = SentencePieceTokenTypes.UNUSED
            elif tokenizer.IsByte(token_id):
                toktype = SentencePieceTokenTypes.BYTE
+            # take care of ununsed raw token
+            if piece.startswith('[UNUSED'):
+                toktype = SentencePieceTokenTypes.UNKNOWN

            tokens.append(text)
            scores.append(score)
@ -2170,6 +2169,47 @@ class InternLM2Model(Model):
                    scores.append(-1000.0)
                    toktypes.append(SentencePieceTokenTypes.USER_DEFINED)

+        chat_eos_token = '<|im_end|>'
+        chat_eos_token_id = None
+
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+                added_tokens_decoder = tokenizer_config_json.get("added_tokens_decoder", {})
+                for token_id, foken_data in added_tokens_decoder.items():
+                    token_id = int(token_id)
+                    token = foken_data["content"]
+                    if token == chat_eos_token:
+                        chat_eos_token_id = token_id
+                    token = token.encode("utf-8")
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                        assert(tokens[token_id] == token)
+                    tokens[token_id] = token
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+                    if foken_data.get("special"):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+
+        tokenizer_file = self.dir_model / 'tokenizer.json'
+        if tokenizer_file.is_file():
+            with open(tokenizer_file, "r", encoding="utf-8") as f:
+                tokenizer_json = json.load(f)
+                added_tokens = tokenizer_json.get("added_tokens", [])
+                for foken_data in added_tokens:
+                    token_id = int(foken_data["id"])
+                    token = foken_data["content"]
+                    if token == chat_eos_token:
+                        chat_eos_token_id = token_id
+                    token = token.encode("utf-8")
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                        assert(tokens[token_id] == token)
+                    tokens[token_id] = token
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+                    if foken_data.get("special"):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+
        self.gguf_writer.add_tokenizer_model("llama")
        self.gguf_writer.add_tokenizer_pre("default")
        self.gguf_writer.add_token_list(tokens)
@ -2179,28 +2219,16 @@ class InternLM2Model(Model):

        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
        old_eos = special_vocab.special_token_ids["eos"]
-        if "chat" in os.path.basename(self.dir_model.absolute()):
+        if chat_eos_token_id is not None:
            # For the chat model, we replace the eos with '<|im_end|>'.
            # TODO: this is a hack, should be fixed
            #       https://github.com/ggerganov/llama.cpp/pull/6745#issuecomment-2067687048
-            special_vocab.special_token_ids["eos"] = self._try_get_sft_eos(tokenizer)
-            logger.warning(f"Replace eos:{old_eos} with a special token:{special_vocab.special_token_ids['eos']} \
-in chat mode so that the conversation can end normally.")
+            special_vocab.special_token_ids["eos"] = chat_eos_token_id
+            logger.warning(f"Replace eos:{old_eos} with a special token:{chat_eos_token_id}"
+                           " in chat mode so that the conversation can end normally.")

        special_vocab.add_to_gguf(self.gguf_writer)

-    def _try_get_sft_eos(self, tokenizer):
-        unused_145_list = tokenizer.Encode('[UNUSED_TOKEN_145]')
-        im_end_list = tokenizer.Encode('<|im_end|>')
-        eos_token = None
-        assert (len(unused_145_list) == 1) ^ (len(im_end_list) == 1)
-        if len(unused_145_list) == 1:
-            eos_token = unused_145_list[0]
-        if len(im_end_list) == 1:
-            eos_token = im_end_list[0]
-        assert eos_token
-        return eos_token
-
    def _hf_permute_qk(self, weights, n_head: int, n_head_kv: int):
        if n_head_kv is not None and n_head != n_head_kv:
            n_head = n_head_kv
@ -2219,6 +2247,10 @@ in chat mode so that the conversation can end normally.")
        self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
        self.gguf_writer.add_head_count_kv(self.hparams["num_key_value_heads"])
        self.gguf_writer.add_file_type(self.ftype)
+        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
+            if self.hparams["rope_scaling"].get("type") == "linear":
+                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])

    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
        num_heads = self.hparams["num_attention_heads"]
@ -2979,16 +3011,16 @@ class T5Model(Model):
        if not tokenizer_path.is_file():
            raise FileNotFoundError(f"File not found: {tokenizer_path}")

-        sentencepiece_model = model.ModelProto()
+        sentencepiece_model = model.ModelProto()  # pyright: ignore[reportAttributeAccessIssue]
        sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read())

        # some models like Pile-T5 family use BPE tokenizer instead of Unigram
-        if sentencepiece_model.trainer_spec.model_type == 2: # BPE
+        if sentencepiece_model.trainer_spec.model_type == 2:  # BPE
            # assure the tokenizer model file name is correct
            assert tokenizer_path.name == 'tokenizer.model'
            return self._set_vocab_sentencepiece()
        else:
-            assert sentencepiece_model.trainer_spec.model_type == 1 # UNIGRAM
+            assert sentencepiece_model.trainer_spec.model_type == 1  # UNIGRAM

        add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix
        remove_whitespaces = sentencepiece_model.normalizer_spec.remove_extra_whitespaces
@ -3159,7 +3191,7 @@ class JaisModel(Model):
            # but Jais's PyTorch model simply precalculates the slope values and places them
            # in relative_pes.slopes
            n_head_closest_log2 = 2 ** math.floor(math.log2(self.hparams["n_head"]))
-            first_val = float(data_torch._data[0])
+            first_val = float(data_torch[0].item())
            self.max_alibi_bias = -round(math.log2(first_val) * n_head_closest_log2)

            return tensors
@ -3193,7 +3225,7 @@ class ChatGLMModel(Model):
    def set_vocab_chatglm3(self):
        dir_model = self.dir_model
        hparams = self.hparams
-        tokens: list[bytearray] = []
+        tokens: list[bytes] = []
        toktypes: list[int] = []
        scores: list[float] = []

@ -3342,7 +3374,7 @@ class ChatGLMModel(Model):
        special_vocab.add_to_gguf(self.gguf_writer)

    def set_gguf_parameters(self):
-        self.gguf_writer.add_name(self.hparams.get("_name_or_path").split("/")[1]) # THUDM/glm4-9b-chat or THUDM/chatglm3-6b
+        self.gguf_writer.add_name(self.hparams["_name_or_path"].split("/")[1]) # THUDM/glm4-9b-chat or THUDM/chatglm3-6b
        n_embed = self.hparams.get("hidden_size", self.hparams.get("n_embed"))
        n_head = self.hparams.get("n_head", self.hparams.get("num_attention_heads"))
        n_head_kv = self.hparams.get("multi_query_group_num", n_head)
--- a/convert_llama_ggml_to_gguf.py
+++ b/convert_llama_ggml_to_gguf.py
@ -354,7 +354,8 @@ class GGMLToGGUF:


 def handle_metadata(cfg, hp):
-    import convert
+    import examples.convert_legacy_llama as convert
+
    assert cfg.model_metadata_dir.is_dir(), 'Metadata dir is not a directory'
    hf_config_path   = cfg.model_metadata_dir / "config.json"
    orig_config_path = cfg.model_metadata_dir / "params.json"
--- a/docs/build.md
+++ b/docs/build.md
@ -28,6 +28,7 @@ In order to build llama.cpp you have four different options.
        ```

  - Notes:
+    - For `Q4_0_4_4` quantization type build, add the `GGML_NO_LLAMAFILE=1` flag. For example, use `make GGML_NO_LLAMAFILE=1`.
    - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `make -j 8` will run 8 jobs in parallel.
    - For faster repeated compilation, install [ccache](https://ccache.dev/).
    - For debug builds, run `make LLAMA_DEBUG=1`
@ -41,6 +42,7 @@ In order to build llama.cpp you have four different options.

  **Notes**:

+    - For `Q4_0_4_4` quantization type build, add the `-DGGML_LLAMAFILE=OFF` cmake option. For example, use `cmake -B build -DGGML_LLAMAFILE=OFF`.
    - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `cmake --build build --config Release -j 8` will run 8 jobs in parallel.
    - For faster repeated compilation, install [ccache](https://ccache.dev/).
    - For debug builds, there are two cases:
--- a/examples/convert_legacy_llama.py
+++ b/examples/convert_legacy_llama.py
@ -353,7 +353,7 @@ class Metadata:
    version: Optional[str] = None
    url: Optional[str] = None
    description: Optional[str] = None
-    licence: Optional[str] = None
+    license: Optional[str] = None
    source_url: Optional[str] = None
    source_hf_repo: Optional[str] = None

@ -492,12 +492,13 @@ class LazyTensor:

 LazyModel: TypeAlias = 'dict[str, LazyTensor]'

+ModelFormat: TypeAlias = Literal['ggml', 'torch', 'safetensors', 'none']

@dataclass
 class ModelPlus:
    model: LazyModel
    paths: list[Path]  # Where this was read from.
-    format: Literal['ggml', 'torch', 'safetensors', 'none']
+    format: ModelFormat
    vocab: BaseVocab | None  # For GGML models (which have vocab built in), the vocab.


@ -536,7 +537,7 @@ def merge_sharded(models: list[LazyModel]) -> LazyModel:


 def merge_multifile_models(models_plus: list[ModelPlus]) -> ModelPlus:
-    formats = set(mp.format for mp in models_plus)
+    formats: set[ModelFormat] = set(mp.format for mp in models_plus)
    assert len(formats) == 1, "different formats?"
    format = formats.pop()
    paths = [path for mp in models_plus for path in mp.paths]
@ -555,7 +556,7 @@ def merge_multifile_models(models_plus: list[ModelPlus]) -> ModelPlus:
    else:
        model = merge_sharded([mp.model for mp in models_plus])

-    return ModelPlus(model, paths, format, vocab)  # pytype: disable=wrong-arg-types
+    return ModelPlus(model, paths, format, vocab)


 def permute_lazy(lazy_tensor: LazyTensor, n_head: int, n_head_kv: int) -> LazyTensor:
@ -805,7 +806,7 @@ class OutputFile:
    def __init__(self, fname_out: Path, endianess:gguf.GGUFEndian = gguf.GGUFEndian.LITTLE):
        self.gguf = gguf.GGUFWriter(fname_out, gguf.MODEL_ARCH_NAMES[ARCH], endianess=endianess)

-    def add_meta_model(self, params: Params, metadata: Metadata) -> None:
+    def add_meta_model(self, params: Params, metadata: Metadata | None) -> None:
        # Metadata About The Model And Its Provenence
        name = "LLaMA"
        if metadata is not None and metadata.name is not None:
@ -827,8 +828,8 @@ class OutputFile:
                self.gguf.add_url(metadata.url)
            if metadata.description is not None:
                self.gguf.add_description(metadata.description)
-            if metadata.licence is not None:
-                self.gguf.add_licence(metadata.licence)
+            if metadata.license is not None:
+                self.gguf.add_licence(metadata.license)
            if metadata.source_url is not None:
                self.gguf.add_source_url(metadata.source_url)
            if metadata.source_hf_repo is not None:
@ -943,7 +944,7 @@ class OutputFile:
    @staticmethod
    def write_vocab_only(
        fname_out: Path, params: Params, vocab: Vocab, svocab: gguf.SpecialVocab,
-        endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, metadata: Metadata = None,
+        endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, metadata: Metadata | None = None,
    ) -> None:
        check_vocab_size(params, vocab, pad_vocab=pad_vocab)

@ -977,7 +978,7 @@ class OutputFile:
        fname_out: Path, ftype: GGMLFileType, params: Params, model: LazyModel, vocab: BaseVocab, svocab: gguf.SpecialVocab,
        concurrency: int = DEFAULT_CONCURRENCY, endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE,
        pad_vocab: bool = False,
-        metadata: Metadata = None,
+        metadata: Metadata | None = None,
    ) -> None:
        check_vocab_size(params, vocab, pad_vocab=pad_vocab)

@ -1396,6 +1397,8 @@ def main(args_in: list[str] | None = None) -> None:
    if model_plus.vocab is not None and args.vocab_dir is None and not args.no_vocab:
        vocab = model_plus.vocab

+    assert params is not None
+
    logger.info(f"Vocab info: {vocab}")
    logger.info(f"Special vocab info: {special_vocab}")
    model   = model_plus.model
--- a/examples/deprecation-warning/README.md
+++ b/examples/deprecation-warning/README.md
@ -0,0 +1,51 @@
+# Migration notice for binary filenames
+
+> [!IMPORTANT]
+[2024 Jun 12] Binaries have been renamed w/ a `llama-` prefix. `main` is now `llama-cli`, `server` is `llama-server`, etc (https://github.com/ggerganov/llama.cpp/pull/7809)
+
+This migration was important, but it is a breaking change that may not always be immediately obvious to users.
+
+Please update all scripts and workflows to use the new binary names.
+
+| Old Filename | New Filename |
+| ---- | ---- |
+| main | llama-cli |
+| server | llama-server |
+| llama-bench | llama-bench |
+| embedding | llama-embedding |
+| finetune | llama-finetune |
+| quantize | llama-quantize |
+| tokenize | llama-tokenize |
+| export-lora | llama-export-lora |
+| libllava.a | libllava.a |
+| baby-llama | llama-baby-llama |
+| batched | llama-batched |
+| batched-bench | llama-batched-bench |
+| benchmark-matmult | llama-benchmark-matmult |
+| convert-llama2c-to-ggml | llama-convert-llama2c-to-ggml |
+| eval-callback | llama-eval-callback |
+| gbnf-validator | llama-gbnf-validator |
+| gguf | llama-gguf |
+| gguf-split | llama-gguf-split |
+| gritlm | llama-gritlm |
+| imatrix | llama-imatrix |
+| infill | llama-infill |
+| llava-cli | llama-llava-cli |
+| lookahead | llama-lookahead |
+| lookup | llama-lookup |
+| lookup-create | llama-lookup-create |
+| lookup-merge | llama-lookup-merge |
+| lookup-stats | llama-lookup-stats |
+| parallel | llama-parallel |
+| passkey | llama-passkey |
+| perplexity | llama-perplexity |
+| q8dot | llama-q8dot |
+| quantize-stats | llama-quantize-stats |
+| retrieval | llama-retrieval |
+| save-load-state | llama-save-load-state |
+| simple | llama-simple |
+| speculative | llama-speculative |
+| train-text-from-scratch | llama-train-text-from-scratch |
+| vdot | llama-vdot |
+| tests/test-c.o | tests/test-c.o |
+
--- a/examples/deprecation-warning/deprecation-warning.cpp
+++ b/examples/deprecation-warning/deprecation-warning.cpp
@ -0,0 +1,35 @@
+// Warns users that this filename was deprecated, and provides a link for more information.
+
+#include <cstdio>
+#include <string>
+#include <unordered_map>
+
+// Main
+int main(int argc, char** argv) {
+    std::string filename = "main";
+    if (argc >= 1) {
+        filename = argv[0];
+    }
+
+    // Get only the program name from the full path
+    auto pos = filename.find_last_of('/');
+    if (pos != std::string::npos) {
+        filename = filename.substr(pos+1);
+    }
+
+    // Append "llama-" to the beginning of filename to get the replacemnt filename
+    auto replacement_filename = "llama-" + filename;
+
+    // The exception is if the filename is "main", then our replacement filename is "llama-cli"
+    if (filename == "main") {
+        replacement_filename = "llama-cli";
+    }
+
+    fprintf(stdout, "\n");
+    fprintf(stdout, "WARNING: The binary '%s' is deprecated.\n", filename.c_str());
+    fprintf(stdout, " Please use '%s' instead.\n", replacement_filename.c_str());
+    fprintf(stdout, " See https://github.com/ggerganov/llama.cpp/tree/master/examples/deprecation-warning/README.md for more information.\n");
+    fprintf(stdout, "\n");
+
+    return EXIT_FAILURE;
+}
--- a/examples/finetune/convert_finetune_checkpoint_to_gguf.py
+++ b/examples/finetune/convert_finetune_checkpoint_to_gguf.py
@ -74,7 +74,7 @@ class Tensor:
            if len(self.ne) == 0:
                self.nbytes = 0
            else:
-                self.nbytes = int(np.product(self.ne)) * 4
+                self.nbytes = int(np.prod(self.ne)) * 4
        else:
            raise ValueError(f"Unhandled data type '{self.dtype}'")

--- a/examples/infill/infill.cpp
+++ b/examples/infill/infill.cpp
@ -204,21 +204,17 @@ int main(int argc, char ** argv) {
    GGML_ASSERT(llama_add_eos_token(model) != 1);
    LOG("add_bos: %d\n", add_bos);

-    bool suff_rm_leading_spc = params.escape;
-    if (suff_rm_leading_spc && params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
-        params.input_suffix.erase(0, 1);
-        suff_rm_leading_spc = false;
-    }
    std::vector<llama_token> embd_inp;
    std::vector<llama_token> embd_end;
    std::vector<llama_token> inp_pfx = ::llama_tokenize(ctx, params.input_prefix, false);
    std::vector<llama_token> inp_sfx = ::llama_tokenize(ctx, params.input_suffix, false);
-    const int space_token = 29871;
-    if (suff_rm_leading_spc && inp_sfx[0] == space_token) {
-        inp_sfx.erase(inp_sfx.begin());
-    }
+
+    GGML_ASSERT(llama_token_prefix(model) >= 0);
+    GGML_ASSERT(llama_token_suffix(model) >= 0);
+
    inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(model));
    inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
+
    embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
    embd_end = params.spm_infill ? inp_pfx : inp_sfx;
    if (add_bos) {
@ -516,19 +512,14 @@ int main(int argc, char ** argv) {
                    string_process_escapes(params.input_prefix);
                    string_process_escapes(params.input_suffix);
                }
-                suff_rm_leading_spc = params.escape;
-                if (suff_rm_leading_spc && params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
-                    params.input_suffix.erase(0, 1);
-                    suff_rm_leading_spc = false;
-                }
+
                // tokenize new prefix and suffix
                std::vector<llama_token> inp_pfx = ::llama_tokenize(ctx, params.input_prefix, false);
                std::vector<llama_token> inp_sfx = ::llama_tokenize(ctx, params.input_suffix, false);
-                if (suff_rm_leading_spc && inp_sfx[0] == space_token) {
-                    inp_sfx.erase(inp_sfx.begin());
-                }
+
                inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(model));
                inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
+
                embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
                embd_end = params.spm_infill ? inp_pfx : inp_sfx;
                if (add_bos) {
--- a/examples/json_schema_pydantic_example.py
+++ b/examples/json_schema_pydantic_example.py
@ -3,7 +3,7 @@
 #! pip install pydantic
 #! python json_schema_pydantic_example.py

-from pydantic import BaseModel, Extra, TypeAdapter
+from pydantic import BaseModel, Field, TypeAdapter
 from annotated_types import MinLen
 from typing import Annotated, List, Optional
 import json, requests
@ -17,6 +17,9 @@ if True:

        The response_model param takes a type (+ supports Pydantic) and behaves just as w/ Instructor (see below)
        '''
+        response_format = None
+        type_adapter = None
+
        if response_model:
            type_adapter = TypeAdapter(response_model)
            schema = type_adapter.json_schema()
--- a/examples/json_schema_to_grammar.py
+++ b/examples/json_schema_to_grammar.py
@ -1,4 +1,6 @@
 #!/usr/bin/env python3
+from __future__ import annotations
+
 import argparse
 import itertools
 import json
@ -188,7 +190,7 @@ def _generate_min_max_int(min_value: Optional[int], max_value: Optional[int], ou
    raise RuntimeError("At least one of min_value or max_value must be set")

 class BuiltinRule:
-    def __init__(self, content: str, deps: list = None):
+    def __init__(self, content: str, deps: list | None = None):
        self.content = content
        self.deps = deps or []

@ -248,7 +250,7 @@ class SchemaConverter:

    def _format_literal(self, literal):
        escaped = GRAMMAR_LITERAL_ESCAPE_RE.sub(
-            lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)), literal
+            lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)) or m.group(0), literal
        )
        return f'"{escaped}"'

@ -403,11 +405,11 @@ class SchemaConverter:
        i = 0
        length = len(pattern)

-        def to_rule(s: Tuple[str, bool]) -> str:
+        def to_rule(s: tuple[str, bool]) -> str:
            (txt, is_literal) = s
            return "\"" + txt + "\"" if is_literal else txt

-        def transform() -> Tuple[str, bool]:
+        def transform() -> tuple[str, bool]:
            '''
                Parse a unit at index i (advancing it), and return its string representation + whether it's a literal.
            '''
@ -420,7 +422,7 @@ class SchemaConverter:
            # We only need a flat structure here to apply repetition operators to the last item, and
            # to merge literals at the and (we're parsing grouped ( sequences ) recursively and don't treat '|' specially
            # (GBNF's syntax is luckily very close to regular expressions!)
-            seq: list[Tuple[str, bool]] = []
+            seq: list[tuple[str, bool]] = []

            def get_dot():
                if self._dotall:
--- a/examples/llava/convert_image_encoder_to_gguf.py
+++ b/examples/llava/convert_image_encoder_to_gguf.py
@ -185,6 +185,8 @@ else:
    fout.add_description("two-tower CLIP model")

 if has_text_encoder:
+    assert t_hparams is not None
+    assert tokens is not None
    # text_model hparams
    fout.add_uint32(k(KEY_CONTEXT_LENGTH, TEXT), t_hparams["max_position_embeddings"])
    fout.add_uint32(k(KEY_EMBEDDING_LENGTH, TEXT), t_hparams["hidden_size"])
@ -259,8 +261,8 @@ if has_vision_encoder:


    if processor is not None:
-        image_mean = processor.image_processor.image_mean if args.image_mean is None or args.image_mean == default_image_mean else args.image_mean
-        image_std = processor.image_processor.image_std if args.image_std is None or args.image_std == default_image_std else args.image_std
+        image_mean = processor.image_processor.image_mean if args.image_mean is None or args.image_mean == default_image_mean else args.image_mean  # pyright: ignore[reportAttributeAccessIssue]
+        image_std = processor.image_processor.image_std if args.image_std is None or args.image_std == default_image_std else args.image_std  # pyright: ignore[reportAttributeAccessIssue]
    else:
        image_mean = args.image_mean if args.image_mean is not None else default_image_mean
        image_std = args.image_std if args.image_std is not None else default_image_std
@ -272,7 +274,7 @@ fout.add_bool("clip.use_gelu", use_gelu)


 if has_llava_projector:
-    model.vision_model.encoder.layers.pop(-1)
+    model.vision_model.encoder.layers.pop(-1)  # pyright: ignore[reportAttributeAccessIssue]
    projector = torch.load(args.llava_projector)
    for name, data in projector.items():
        name = get_tensor_name(name)
@ -286,7 +288,7 @@ if has_llava_projector:

    print("Projector tensors added\n")

-state_dict = model.state_dict()
+state_dict = model.state_dict()  # pyright: ignore[reportAttributeAccessIssue]
 for name, data in state_dict.items():
    if should_skip_tensor(name, has_text_encoder, has_vision_encoder, has_llava_projector):
        # we don't need this
--- a/examples/llava/llava_surgery_v2.py
+++ b/examples/llava/llava_surgery_v2.py
@ -2,7 +2,9 @@ import argparse
 import glob
 import os
 import torch
-from safetensors.torch import load as safe_load, save as safe_save, safe_open, save_file
+from safetensors import safe_open
+from safetensors.torch import save_file
+from typing import Any, ContextManager, cast

 # Function to determine if file is a SafeTensor file
 def is_safetensor_file(file_path):
@ -13,7 +15,7 @@ def is_safetensor_file(file_path):
 def load_model(file_path):
    if is_safetensor_file(file_path):
        tensors = {}
-        with safe_open(file_path, framework="pt", device="cpu") as f:
+        with cast(ContextManager[Any], safe_open(file_path, framework="pt", device="cpu")) as f:
            for key in f.keys():
                tensors[key] = f.get_tensor(key).clone()
                # output shape
@ -134,7 +136,7 @@ if len(mm_tensors) == 0:
    if last_checkpoint is not None:
        for k, v in last_checkpoint.items():
            print(k)
-    print(f"Found {len(mm_tensors)} tensors to extract out of {len(last_checkpoint)} tensors.")
+    print(f"Found {len(mm_tensors)} tensors to extract out of {len(last_checkpoint) if last_checkpoint is not None else 0} tensors.")
    print("No tensors found. Is this a LLaVA model?")
    exit()

@ -143,8 +145,10 @@ print(f"Found additional {len(first_mm_tensors)} tensors to extract.")
 # projector = {name: checkpoint.[name].float() for name in mm_tensors}
 projector = {}
 for name in mm_tensors:
+    assert last_checkpoint is not None
    projector[name] = last_checkpoint[name].float()
 for name in first_mm_tensors:
+    assert first_checkpoint is not None
    projector[name] = first_checkpoint[name].float()

 if len(projector) > 0:
--- a/examples/pydantic_models_to_grammar.py
+++ b/examples/pydantic_models_to_grammar.py
@ -6,10 +6,10 @@ import re
 from copy import copy
 from enum import Enum
 from inspect import getdoc, isclass
-from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin, get_type_hints
+from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin

 from docstring_parser import parse
-from pydantic import BaseModel, Field, create_model
+from pydantic import BaseModel, create_model

 if TYPE_CHECKING:
    from types import GenericAlias
@ -17,6 +17,9 @@ else:
    # python 3.8 compat
    from typing import _GenericAlias as GenericAlias

+# TODO: fix this
+# pyright: reportAttributeAccessIssue=information
+

 class PydanticDataType(Enum):
    """
@ -234,8 +237,9 @@ def generate_gbnf_float_rules(max_digit=None, min_digit=None, max_precision=None

    # Define the integer part rule
    integer_part_rule = (
-        "integer-part" + (f"-max{max_digit}" if max_digit is not None else "") + (
-        f"-min{min_digit}" if min_digit is not None else "")
+        "integer-part"
+        + (f"-max{max_digit}" if max_digit is not None else "")
+        + (f"-min{min_digit}" if min_digit is not None else "")
    )

    # Define the fractional part rule based on precision constraints
@ -458,7 +462,7 @@ def generate_gbnf_grammar(model: type[BaseModel], processed_models: set[type[Bas
    if not issubclass(model, BaseModel):
        # For non-Pydantic classes, generate model_fields from __annotations__ or __init__
        if hasattr(model, "__annotations__") and model.__annotations__:
-            model_fields = {name: (typ, ...) for name, typ in model.__annotations__.items()}
+            model_fields = {name: (typ, ...) for name, typ in model.__annotations__.items()}  # pyright: ignore[reportGeneralTypeIssues]
        else:
            init_signature = inspect.signature(model.__init__)
            parameters = init_signature.parameters
@ -680,7 +684,7 @@ def generate_markdown_documentation(
        str: Generated text documentation.
    """
    documentation = ""
-    pyd_models = [(model, True) for model in pydantic_models]
+    pyd_models: list[tuple[type[BaseModel], bool]] = [(model, True) for model in pydantic_models]
    for model, add_prefix in pyd_models:
        if add_prefix:
            documentation += f"{model_prefix}: {model.__name__}\n"
@ -700,7 +704,7 @@ def generate_markdown_documentation(
            # Indenting the fields section
            documentation += f"  {fields_prefix}:\n"
        else:
-            documentation += f"  Fields:\n"
+            documentation += f"  Fields:\n"  # noqa: F541
        if isclass(model) and issubclass(model, BaseModel):
            for name, field_type in model.__annotations__.items():
                # if name == "markdown_code_block":
@ -778,7 +782,7 @@ def generate_field_markdown(
        return field_text

    if field_description != "":
-        field_text += f"        Description: " + field_description + "\n"
+        field_text += f"        Description: {field_description}\n"

    # Check for and include field-specific examples if available
    if hasattr(model, "Config") and hasattr(model.Config,
@ -833,7 +837,7 @@ def generate_text_documentation(
        str: Generated text documentation.
    """
    documentation = ""
-    pyd_models = [(model, True) for model in pydantic_models]
+    pyd_models: list[tuple[type[BaseModel], bool]] = [(model, True) for model in pydantic_models]
    for model, add_prefix in pyd_models:
        if add_prefix:
            documentation += f"{model_prefix}: {model.__name__}\n"
@ -1164,7 +1168,7 @@ def create_dynamic_model_from_function(func: Callable[..., Any]):
        dynamic_fields[param.name] = (
            param.annotation if param.annotation != inspect.Parameter.empty else str, default_value)
    # Creating the dynamic model
-    dynamic_model = create_model(f"{func.__name__}", **dynamic_fields)  # type: ignore[call-overload]
+    dynamic_model = create_model(f"{func.__name__}", **dynamic_fields)

    for name, param_doc in param_docs:
        dynamic_model.model_fields[name].description = param_doc.description
@ -1228,9 +1232,6 @@ def map_grammar_names_to_pydantic_model_class(pydantic_model_list):
    return output


-from enum import Enum
-
-
 def json_schema_to_python_types(schema):
    type_map = {
        "any": Any,
@ -1275,7 +1276,7 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
                    if items != {}:
                        array = {"properties": items}
                        array_type = convert_dictionary_to_pydantic_model(array, f"{model_name}_{field_name}_items")
-                        fields[field_name] = (List[array_type], ...)  # type: ignore[valid-type]
+                        fields[field_name] = (List[array_type], ...)
                    else:
                        fields[field_name] = (list, ...)
                elif field_type == "object":
@ -1285,7 +1286,8 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
                    required = field_data.get("enum", [])
                    for key, field in fields.items():
                        if key not in required:
-                            fields[key] = (Optional[fields[key][0]], ...)
+                            optional_type = fields[key][0]
+                            fields[key] = (Optional[optional_type], ...)
                else:
                    field_type = json_schema_to_python_types(field_type)
                    fields[field_name] = (field_type, ...)
@ -1305,6 +1307,7 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
        required = dictionary.get("required", [])
        for key, field in fields.items():
            if key not in required:
-                fields[key] = (Optional[fields[key][0]], ...)
+                optional_type = fields[key][0]
+                fields[key] = (Optional[optional_type], ...)
    custom_model = create_model(model_name, **fields)
    return custom_model
--- a/examples/pydantic_models_to_grammar_examples.py
+++ b/examples/pydantic_models_to_grammar_examples.py
@ -1,6 +1,7 @@
 # Function calling example using pydantic models.
+from __future__ import annotations
+
 import datetime
-import importlib
 import json
 from enum import Enum
 from typing import Optional, Union
@ -215,9 +216,9 @@ for call in json_data:
    if call["function"] == "Calculator":
        print(Calculator(**call["params"]).run())
    elif call["function"] == "get_current_datetime":
-        print(current_datetime_model(**call["params"]).run())
+        print(current_datetime_model(**call["params"]).run())  # pyright: ignore[reportAttributeAccessIssue]
    elif call["function"] == "get_current_weather":
-        print(current_weather_tool_model(**call["params"]).run())
+        print(current_weather_tool_model(**call["params"]).run())  # pyright: ignore[reportAttributeAccessIssue]
 # Should output something like this:
 # 2024-01-14 13:36:06
 # {"location": "London", "temperature": "42", "unit": "celsius"}
--- a/examples/quantize/quantize.cpp
+++ b/examples/quantize/quantize.cpp
@ -46,6 +46,9 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = {
    { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 5.33G, +0.0569 ppl @ Llama-3-8B",  },
    { "Q6_K",   LLAMA_FTYPE_MOSTLY_Q6_K,   " 6.14G, +0.0217 ppl @ Llama-3-8B",  },
    { "Q8_0",   LLAMA_FTYPE_MOSTLY_Q8_0,   " 7.96G, +0.0026 ppl @ Llama-3-8B",  },
+    { "Q4_0_4_4", LLAMA_FTYPE_MOSTLY_Q4_0_4_4, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
+    { "Q4_0_4_8", LLAMA_FTYPE_MOSTLY_Q4_0_4_8, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
+    { "Q4_0_8_8", LLAMA_FTYPE_MOSTLY_Q4_0_8_8, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
    { "F16",    LLAMA_FTYPE_MOSTLY_F16,    "14.00G, +0.0020 ppl @ Mistral-7B",  },
    { "BF16",   LLAMA_FTYPE_MOSTLY_BF16,   "14.00G, -0.0050 ppl @ Mistral-7B",  },
    { "F32",    LLAMA_FTYPE_ALL_F32,       "26.00G              @ 7B",          },
--- a/examples/server/bench/bench.py
+++ b/examples/server/bench/bench.py
@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import argparse
 import json
 import os
@ -59,10 +61,11 @@ def main(args_in: list[str] | None = None) -> None:
        sys.exit(1)

    # start the benchmark
+    iterations = 0
+    data = {}
    try:
        start_benchmark(args)

-        iterations = 0
        with open("results.github.env", 'w') as github_env:
            # parse output
            with open('k6-results.json', 'r') as bench_results:
@ -129,7 +132,7 @@ def main(args_in: list[str] | None = None) -> None:
                timestamps, metric_values = zip(*values)
                metric_values = [float(value) for value in metric_values]
                prometheus_metrics[metric] = metric_values
-                timestamps_dt = [datetime.fromtimestamp(int(ts)) for ts in timestamps]
+                timestamps_dt = [str(datetime.fromtimestamp(int(ts))) for ts in timestamps]
                plt.figure(figsize=(16, 10), dpi=80)
                plt.plot(timestamps_dt, metric_values, label=metric)
                plt.xticks(rotation=0, fontsize=14, horizontalalignment='center', alpha=.7)
@ -156,7 +159,7 @@ def main(args_in: list[str] | None = None) -> None:
                plt.close()

                # Mermaid format in case images upload failed
-                with (open(f"{metric}.mermaid", 'w') as mermaid_f):
+                with open(f"{metric}.mermaid", 'w') as mermaid_f:
                    mermaid = (
                    f"""---
 config:
@ -278,7 +281,7 @@ def start_server_background(args):
    }
    server_process = subprocess.Popen(
        args,
-        **pkwargs)
+        **pkwargs)  # pyright: ignore[reportArgumentType, reportCallIssue]

    def server_log(in_stream, out_stream):
        for line in iter(in_stream.readline, b''):
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@ -884,7 +884,8 @@ struct server_context {

    bool launch_slot_with_task(server_slot & slot, const server_task & task) {
        slot_params default_params;
-        llama_sampling_params default_sparams;
+        // Sampling parameter defaults are loaded from the global server context (but individual requests can still override them)
+        llama_sampling_params default_sparams = params.sparams;
        auto & data = task.data;

        if (data.count("__oaicompat") != 0) {
--- a/examples/server/tests/features/steps/steps.py
+++ b/examples/server/tests/features/steps/steps.py
@ -1,5 +1,4 @@
 import asyncio
-import collections
 import json
 import os
 import re
@ -8,19 +7,23 @@ import subprocess
 import sys
 import threading
 import time
+from collections.abc import Sequence
 from contextlib import closing
 from re import RegexFlag
+from typing import Any, Literal, cast

 import aiohttp
 import numpy as np
 import openai
-from behave import step
+from openai.types.chat import ChatCompletionChunk
+from behave import step  # pyright: ignore[reportAttributeAccessIssue]
 from behave.api.async_step import async_run_until_complete
 from prometheus_client import parser

+# pyright: reportRedeclaration=false

@step("a server listening on {server_fqdn}:{server_port}")
-def step_server_config(context, server_fqdn, server_port):
+def step_server_config(context, server_fqdn: str, server_port: str):
    context.server_fqdn = server_fqdn
    context.server_port = int(server_port)
    context.n_threads = None
@ -74,34 +77,34 @@ def step_server_config(context, server_fqdn, server_port):


@step('a model file {hf_file} from HF repo {hf_repo}')
-def step_download_hf_model(context, hf_file, hf_repo):
+def step_download_hf_model(context, hf_file: str, hf_repo: str):
    context.model_hf_repo = hf_repo
    context.model_hf_file = hf_file
    context.model_file = os.path.basename(hf_file)


@step('a model file {model_file}')
-def step_model_file(context, model_file):
+def step_model_file(context, model_file: str):
    context.model_file = model_file


@step('a model url {model_url}')
-def step_model_url(context, model_url):
+def step_model_url(context, model_url: str):
    context.model_url = model_url


@step('a model alias {model_alias}')
-def step_model_alias(context, model_alias):
+def step_model_alias(context, model_alias: str):
    context.model_alias = model_alias


@step('{seed:d} as server seed')
-def step_seed(context, seed):
+def step_seed(context, seed: int):
    context.server_seed = seed


@step('{ngl:d} GPU offloaded layers')
-def step_n_gpu_layer(context, ngl):
+def step_n_gpu_layer(context, ngl: int):
    if 'N_GPU_LAYERS' in os.environ:
        new_ngl = int(os.environ['N_GPU_LAYERS'])
        if context.debug:
@ -111,37 +114,37 @@ def step_n_gpu_layer(context, ngl):


@step('{n_threads:d} threads')
-def step_n_threads(context, n_threads):
+def step_n_threads(context, n_threads: int):
    context.n_thread = n_threads


@step('{draft:d} as draft')
-def step_draft(context, draft):
+def step_draft(context, draft: int):
    context.draft = draft


@step('{n_ctx:d} KV cache size')
-def step_n_ctx(context, n_ctx):
+def step_n_ctx(context, n_ctx: int):
    context.n_ctx = n_ctx


@step('{n_slots:d} slots')
-def step_n_slots(context, n_slots):
+def step_n_slots(context, n_slots: int):
    context.n_slots = n_slots


@step('{n_predict:d} server max tokens to predict')
-def step_server_n_predict(context, n_predict):
+def step_server_n_predict(context, n_predict: int):
    context.n_server_predict = n_predict


@step('{slot_save_path} as slot save path')
-def step_slot_save_path(context, slot_save_path):
+def step_slot_save_path(context, slot_save_path: str):
    context.slot_save_path = slot_save_path


@step('using slot id {id_slot:d}')
-def step_id_slot(context, id_slot):
+def step_id_slot(context, id_slot: int):
    context.id_slot = id_slot


@ -191,7 +194,7 @@ def step_start_server(context):

@step("the server is {expecting_status}")
@async_run_until_complete
-async def step_wait_for_the_server_to_be_started(context, expecting_status):
+async def step_wait_for_the_server_to_be_started(context, expecting_status: Literal['healthy', 'ready', 'idle', 'busy'] | str):
    match expecting_status:
        case 'healthy':
            await wait_for_health_status(context, context.base_url, 200, 'ok',
@ -221,7 +224,7 @@ async def step_wait_for_the_server_to_be_started(context, expecting_status):

@step('all slots are {expected_slot_status_string}')
@async_run_until_complete
-async def step_all_slots_status(context, expected_slot_status_string):
+async def step_all_slots_status(context, expected_slot_status_string: Literal['idle', 'busy'] | str):
    match expected_slot_status_string:
        case 'idle':
            expected_slot_status = 0
@ -237,7 +240,7 @@ async def step_all_slots_status(context, expected_slot_status_string):

@step('a completion request with {api_error} api error')
@async_run_until_complete
-async def step_request_completion(context, api_error):
+async def step_request_completion(context, api_error: Literal['raised'] | str):
    expect_api_error = api_error == 'raised'
    seeds = await completions_seed(context, num_seeds=1)
    completion = await request_completion(context.prompts.pop(),
@ -777,8 +780,8 @@ def step_assert_metric_value(context, metric_name, metric_value):
 def step_available_models(context):
    # openai client always expects an api_key
    openai.api_key = context.user_api_key if context.user_api_key is not None else 'nope'
-    openai.api_base = f'{context.base_url}/v1'
-    context.models = openai.Model.list().data
+    openai.base_url = f'{context.base_url}/v1/'
+    context.models = openai.models.list().data


@step('{n_model:d} models are supported')
@ -789,7 +792,7 @@ def step_supported_models(context, n_model):


@step('model {i_model:d} is {param} {preposition} {param_value}')
-def step_supported_models(context, i_model, param, preposition, param_value):
+def step_supported_models(context, i_model: int, param: Literal['identified', 'trained'] | str, preposition: str, param_value: str):
    assert i_model < len(context.models)
    model = context.models[i_model]

@ -798,7 +801,7 @@ def step_supported_models(context, i_model, param, preposition, param_value):
        case 'identified':
            value = model.id
        case 'trained':
-            value = str(model.meta.n_ctx_train)
+            value = str(model.meta["n_ctx_train"])
        case _:
            assert False, "param {param} not supported"
    assert param_value == value, f"model param {param} {value} != {param_value}"
@ -810,6 +813,7 @@ async def concurrent_requests(context, f_completion, *args, **kwargs):
        print(f"starting {context.n_prompts} concurrent completion requests...")
    assert context.n_prompts > 0
    seeds = await completions_seed(context)
+    assert seeds is not None
    for prompt_no in range(context.n_prompts):
        shifted_args = [context.prompts.pop(), seeds[prompt_no], *args]
        context.concurrent_tasks.append(asyncio.create_task(f_completion(*shifted_args, **kwargs)))
@ -861,7 +865,7 @@ async def request_completion(prompt,
                             id_slot=None,
                             expect_api_error=None,
                             user_api_key=None,
-                             temperature=None):
+                             temperature=None) -> int | dict[str, Any]:
    if debug:
        print(f"Sending completion request: {prompt}")
    origin = "my.super.domain"
@ -899,8 +903,8 @@ async def request_completion(prompt,
 async def oai_chat_completions(user_prompt,
                               seed,
                               system_prompt,
-                               base_url,
-                               base_path,
+                               base_url: str,
+                               base_path: str,
                               async_client,
                               debug=False,
                               temperature=None,
@ -909,7 +913,7 @@ async def oai_chat_completions(user_prompt,
                               enable_streaming=None,
                               response_format=None,
                               user_api_key=None,
-                               expect_api_error=None):
+                               expect_api_error=None) -> int | dict[str, Any]:
    if debug:
        print(f"Sending OAI Chat completions request: {user_prompt}")
    # openai client always expects an api key
@ -989,32 +993,35 @@ async def oai_chat_completions(user_prompt,
    else:
        try:
            openai.api_key = user_api_key
-            openai.api_base = f'{base_url}{base_path}'
-            chat_completion = openai.Completion.create(
+            openai.base_url = f'{base_url}{base_path.removesuffix("chat")}'
+            assert model is not None
+            chat_completion = openai.chat.completions.create(
                messages=payload['messages'],
                model=model,
                max_tokens=n_predict,
                stream=enable_streaming,
-                response_format=payload.get('response_format'),
+                response_format=payload.get('response_format') or openai.NOT_GIVEN,
                seed=seed,
                temperature=payload['temperature']
            )
-        except openai.error.AuthenticationError as e:
+        except openai.AuthenticationError as e:
            if expect_api_error is not None and expect_api_error:
                return 401
            else:
                assert False, f'error raised: {e}'

        if enable_streaming:
+            chat_completion = cast(openai.Stream[ChatCompletionChunk], chat_completion)
            for chunk in chat_completion:
                assert len(chunk.choices) == 1
                delta = chunk.choices[0].delta
-                if 'content' in delta:
-                    completion_response['content'] += delta['content']
+                if delta.content is not None:
+                    completion_response['content'] += delta.content
                    completion_response['timings']['predicted_n'] += 1
                completion_response['truncated'] = chunk.choices[0].finish_reason != 'stop'
        else:
            assert len(chat_completion.choices) == 1
+            assert chat_completion.usage is not None
            completion_response = {
                'content': chat_completion.choices[0].message.content,
                'timings': {
@ -1028,7 +1035,7 @@ async def oai_chat_completions(user_prompt,
    return completion_response


-async def request_embedding(content, seed, base_url=None):
+async def request_embedding(content, seed, base_url=None) -> list[list[float]]:
    async with aiohttp.ClientSession() as session:
        async with session.post(f'{base_url}/embedding',
                                json={
@ -1041,7 +1048,7 @@ async def request_embedding(content, seed, base_url=None):

 async def request_oai_embeddings(input, seed,
                                 base_url=None, user_api_key=None,
-                                 model=None, async_client=False):
+                                 model=None, async_client=False) -> list[list[float]]:
    # openai client always expects an api_key
    user_api_key = user_api_key if user_api_key is not None else 'nope'
    if async_client:
@ -1063,7 +1070,7 @@ async def request_oai_embeddings(input, seed,
                response_json = await response.json()
                assert response_json['model'] == model, f"invalid model received: {response_json['model']}"
                assert response_json['object'] == 'list'
-                if isinstance(input, collections.abc.Sequence):
+                if isinstance(input, Sequence):
                    embeddings = []
                    for an_oai_embeddings in response_json['data']:
                        embeddings.append(an_oai_embeddings['embedding'])
@ -1072,19 +1079,14 @@ async def request_oai_embeddings(input, seed,
                return embeddings
    else:
        openai.api_key = user_api_key
-        openai.api_base = f'{base_url}/v1'
-        oai_embeddings = openai.Embedding.create(
+        openai.base_url = f'{base_url}/v1/'
+        assert model is not None
+        oai_embeddings = openai.embeddings.create(
            model=model,
            input=input,
        )

-        if isinstance(input, collections.abc.Sequence):
-            embeddings = []
-            for an_oai_embeddings in oai_embeddings.data:
-                embeddings.append(an_oai_embeddings.embedding)
-        else:
-            embeddings = [oai_embeddings.data.embedding]
-        return embeddings
+        return [e.embedding for e in oai_embeddings.data]


 def assert_n_tokens_predicted(completion_response, expected_predicted_n=None, re_content=None):
@ -1122,7 +1124,7 @@ def assert_all_predictions_equal(completion_responses):
            if i == j:
                continue
            content_j = response_j['content']
-        assert content_i == content_j, "contents not equal"
+            assert content_i == content_j, "contents not equal"


 def assert_all_predictions_different(completion_responses):
@ -1136,7 +1138,7 @@ def assert_all_predictions_different(completion_responses):
            if i == j:
                continue
            content_j = response_j['content']
-        assert content_i != content_j, "contents not different"
+            assert content_i != content_j, "contents not different"


 def assert_all_token_probabilities_equal(completion_responses):
@ -1153,7 +1155,7 @@ def assert_all_token_probabilities_equal(completion_responses):
                if i == j:
                    continue
                probs_j = response_j['completion_probabilities'][pos]['probs']
-            assert probs_i == probs_j, "contents not equal"
+                assert probs_i == probs_j, "contents not equal"


 async def gather_tasks_results(context):
@ -1343,7 +1345,7 @@ def start_server_background(context):
    }
    context.server_process = subprocess.Popen(
        [str(arg) for arg in [context.server_path, *server_args]],
-        **pkwargs)
+        **pkwargs)  # pyright: ignore[reportArgumentType, reportCallIssue]

    def server_log(in_stream, out_stream):
        for line in iter(in_stream.readline, b''):
--- a/examples/server/tests/requirements.txt
+++ b/examples/server/tests/requirements.txt
@ -1,6 +1,6 @@
 aiohttp~=3.9.3
 behave~=1.2.6
 huggingface_hub~=0.20.3
-numpy~=1.24.4
-openai~=0.25.0
+numpy~=1.26.4
+openai~=1.30.3
 prometheus-client~=0.20.0
--- a/examples/server_embd.py
+++ b/examples/server_embd.py
@ -1,13 +1,15 @@
 import asyncio
+import asyncio.threads
 import requests
 import numpy as np

+
 n = 8

 result = []

 async def requests_post_async(*args, **kwargs):
-    return await asyncio.to_thread(requests.post, *args, **kwargs)
+    return await asyncio.threads.to_thread(requests.post, *args, **kwargs)

 async def main():
    model_url = "http://127.0.0.1:6900"
--- a/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
+++ b/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
@ -66,7 +66,7 @@ class Tensor:
            if len(self.ne) == 0:
                self.nbytes = 0
            else:
-                self.nbytes = int(np.product(self.ne)) * 4
+                self.nbytes = int(np.prod(self.ne)) * 4
        else:
            raise ValueError(f"Unhandled data type '{self.dtype}'")

--- a/flake.lock
+++ b/flake.lock
@ -5,11 +5,11 @@
        "nixpkgs-lib": "nixpkgs-lib"
      },
      "locked": {
-        "lastModified": 1717285511,
-        "narHash": "sha256-iKzJcpdXih14qYVcZ9QC9XuZYnPc6T8YImb6dX166kw=",
+        "lastModified": 1719994518,
+        "narHash": "sha256-pQMhCCHyQGRzdfAkdJ4cIWiw+JNuWsTX7f0ZYSyz0VY=",
        "owner": "hercules-ci",
        "repo": "flake-parts",
-        "rev": "2a55567fcf15b1b1c7ed712a2c6fadaec7412ea8",
+        "rev": "9227223f6d922fee3c7b190b2cc238a99527bbb7",
        "type": "github"
      },
      "original": {
@ -20,11 +20,11 @@
    },
    "nixpkgs": {
      "locked": {
-        "lastModified": 1719506693,
-        "narHash": "sha256-C8e9S7RzshSdHB7L+v9I51af1gDM5unhJ2xO1ywxNH8=",
+        "lastModified": 1720031269,
+        "narHash": "sha256-rwz8NJZV+387rnWpTYcXaRNvzUSnnF9aHONoJIYmiUQ=",
        "owner": "NixOS",
        "repo": "nixpkgs",
-        "rev": "b2852eb9365c6de48ffb0dc2c9562591f652242a",
+        "rev": "9f4128e00b0ae8ec65918efeba59db998750ead6",
        "type": "github"
      },
      "original": {
@ -36,14 +36,14 @@
    },
    "nixpkgs-lib": {
      "locked": {
-        "lastModified": 1717284937,
-        "narHash": "sha256-lIbdfCsf8LMFloheeE6N31+BMIeixqyQWbSr2vk79EQ=",
+        "lastModified": 1719876945,
+        "narHash": "sha256-Fm2rDDs86sHy0/1jxTOKB1118Q0O3Uc7EC0iXvXKpbI=",
        "type": "tarball",
-        "url": "https://github.com/NixOS/nixpkgs/archive/eb9ceca17df2ea50a250b6b27f7bf6ab0186f198.tar.gz"
+        "url": "https://github.com/NixOS/nixpkgs/archive/5daf0514482af3f97abaefc78a6606365c9108e2.tar.gz"
      },
      "original": {
        "type": "tarball",
-        "url": "https://github.com/NixOS/nixpkgs/archive/eb9ceca17df2ea50a250b6b27f7bf6ab0186f198.tar.gz"
+        "url": "https://github.com/NixOS/nixpkgs/archive/5daf0514482af3f97abaefc78a6606365c9108e2.tar.gz"
      }
    },
    "root": {
--- a/ggml/CMakeLists.txt
+++ b/ggml/CMakeLists.txt
@ -104,7 +104,7 @@ option(GGML_ACCELERATE                      "ggml: enable Accelerate framework"
 option(GGML_BLAS                            "ggml: use BLAS"                                  ${GGML_BLAS_DEFAULT})
 set(GGML_BLAS_VENDOR ${GGML_BLAS_VENDOR_DEFAULT} CACHE STRING
                                            "ggml: BLAS library vendor")
-option(GGML_LLAMAFILE                       "ggml: use ggml SGEMM"                            OFF)
+option(GGML_LLAMAFILE                       "ggml: use LLAMAFILE"                             OFF)

 option(GGML_CUDA                            "ggml: use CUDA"                                  OFF)
 option(GGML_CUDA_FORCE_DMMV                 "ggml: use dmmv instead of mmvq CUDA kernels"     OFF)
--- a/ggml/ggml_vk_generate_shaders.py
+++ b/ggml/ggml_vk_generate_shaders.py
@ -99,6 +99,8 @@ async def main():

    tasks = []

+    base_dict = {"FLOAT_TYPE": "float"}
+
    for fp16 in (False, True):
        # MUL_MAT
        matmul_shaders(tasks, fp16, False)
@ -106,8 +108,6 @@ async def main():
        matmul_shaders(tasks, fp16, True)

    for tname in type_names:
-        base_dict = {"FLOAT_TYPE": "float"}
-
        # mul mat vec
        data_a_key = f"DATA_A_{tname.upper()}"
        shader = f"mul_mat_vec_{tname}.comp" if tname.endswith("_k") else "mul_mat_vec.comp"
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@ -383,6 +383,9 @@ extern "C" {
        GGML_TYPE_F64     = 28,
        GGML_TYPE_IQ1_M   = 29,
        GGML_TYPE_BF16    = 30,
+        GGML_TYPE_Q4_0_4_4 = 31,
+        GGML_TYPE_Q4_0_4_8 = 32,
+        GGML_TYPE_Q4_0_8_8 = 33,
        GGML_TYPE_COUNT,
    };

@ -424,6 +427,9 @@ extern "C" {
        GGML_FTYPE_MOSTLY_IQ4_XS  = 22, // except 1d tensors
        GGML_FTYPE_MOSTLY_IQ1_M   = 23, // except 1d tensors
        GGML_FTYPE_MOSTLY_BF16    = 24, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q4_0_4_4 = 25, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q4_0_4_8 = 26, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q4_0_8_8 = 27, // except 1d tensors
    };

    // available tensor operations:
@ -2406,6 +2412,12 @@ extern "C" {
    typedef void (*ggml_from_float_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t k);
    typedef void (*ggml_vec_dot_t)   (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x, size_t bx,
                                      const void * GGML_RESTRICT y, size_t by, int nrc);
+    typedef void (*ggml_from_float_to_mat_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t nr,
+                                             int64_t k, int64_t bx);
+    typedef void (*ggml_gemv_t)      (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
+                                      const void * GGML_RESTRICT y, int nr, int nc);
+    typedef void (*ggml_gemm_t)      (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
+                                      const void * GGML_RESTRICT y, int nr, int nc);

    typedef struct {
        const char      * type_name;
@ -2418,6 +2430,11 @@ extern "C" {
        ggml_vec_dot_t    vec_dot;
        enum ggml_type    vec_dot_type;
        int64_t           nrows; // number of rows to process simultaneously;
+        int64_t           ncols; // number of columns to process simultaneously;
+        int64_t           interleave_blcksize; // interleave elements in blocks of interleave_blcksize;
+        ggml_from_float_to_mat_t from_float_to_mat;
+        ggml_gemv_t       gemv;
+        ggml_gemm_t       gemm;
    } ggml_type_traits_t;

    GGML_API ggml_type_traits_t ggml_internal_get_type_traits(enum ggml_type type);
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@ -238,12 +238,12 @@ if (GGML_BLAS)
 endif()

 if (GGML_LLAMAFILE)
-    message(STATUS "Using ggml SGEMM")
+    message(STATUS "Using llamafile")

    add_compile_definitions(GGML_USE_LLAMAFILE)

-    set(GGML_HEADERS_LLAMAFILE sgemm.h)
-    set(GGML_SOURCES_LLAMAFILE sgemm.cpp)
+    set(GGML_HEADERS_LLAMAFILE llamafile/sgemm.h)
+    set(GGML_SOURCES_LLAMAFILE llamafile/sgemm.cpp)
 endif()

 if (GGML_CUDA)
@ -1153,6 +1153,7 @@ add_library(ggml
            ${GGML_SOURCES_ROCM}      ${GGML_HEADERS_ROCM}
            ${GGML_SOURCES_BLAS}      ${GGML_HEADERS_BLAS}
            ${GGML_SOURCES_LLAMAFILE} ${GGML_HEADERS_LLAMAFILE}
+            ggml-aarch64.c            ggml-aarch64.h
            )

 if (EMSCRIPTEN)
--- a/ggml/src/ggml-aarch64.c
+++ b/ggml/src/ggml-aarch64.c
--- a/ggml/src/ggml-aarch64.h
+++ b/ggml/src/ggml-aarch64.h
@ -0,0 +1,39 @@
+// SPDX-FileCopyrightText: Copyright 2024 Arm Ltd.
+#pragma once
+
+#define GGML_COMMON_DECL_C
+#include "ggml-common.h"
+
+#include "ggml.h"
+
+// GGML internal header
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// Quantization
+void quantize_q8_0_4x4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+
+void quantize_mat_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t nrows, int64_t n_per_row, int64_t interleave_blcksize);
+
+// Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
+size_t quantize_q4_0_4x4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_0_4x8(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_0_8x8(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+
+// GEMV
+void ggml_gemv_q4_0_4x4_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_4x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_8x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+
+// GEMM
+void ggml_gemm_q4_0_4x4_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_4x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_8x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+
+#ifdef __cplusplus
+}
+#endif
+
--- a/ggml/src/ggml-common.h
+++ b/ggml/src/ggml-common.h
@ -199,6 +199,30 @@ typedef struct {
 } block_q8_1;
 static_assert(sizeof(block_q8_1) == 2*sizeof(ggml_half) + QK8_1, "wrong q8_1 block size/padding");

+typedef struct {
+    ggml_half d[4];        // deltas for 4 q4_0 blocks
+    uint8_t qs[QK4_0 * 2]; // nibbles / quants for 4 q4_0 blocks
+} block_q4_0x4;
+static_assert(sizeof(block_q4_0x4) == 4 * sizeof(ggml_half) + QK4_0 * 2, "wrong q4_0x4 block size/padding");
+
+typedef struct {
+    ggml_half d[8];        // deltas for 8 q4_0 blocks
+    uint8_t qs[QK4_0 * 4]; // nibbles / quants for 8 q4_0 blocks
+} block_q4_0x8;
+static_assert(sizeof(block_q4_0x8) == 8 * sizeof(ggml_half) + QK4_0 * 4, "wrong q4_0x8 block size/padding");
+
+typedef struct {
+    ggml_half d[4];        // deltas for 4 q8_0 blocks
+    int8_t qs[QK8_0 * 4];  // quants for 4 q8_0 blocks
+} block_q8_0x4;
+static_assert(sizeof(block_q8_0x4) == 4 * sizeof(ggml_half) + QK8_0 * 4, "wrong q8_0x4 block size/padding");
+
+typedef struct {
+    ggml_half d[8];        // deltas for 8 q8_0 blocks
+    int8_t qs[QK8_0 * 8];  // quants for 8 q8_0 blocks
+} block_q8_0x8;
+static_assert(sizeof(block_q8_0x8) == 8 * sizeof(ggml_half) + QK8_0 * 8, "wrong q8_0x8 block size/padding");
+
 //
 // Super-block quantization structures
 //
--- a/ggml/src/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda.cu
@ -29,6 +29,7 @@
 #include "ggml-cuda/tsembd.cuh"
 #include "ggml-cuda/unary.cuh"
 #include "ggml-cuda/upscale.cuh"
+#include "ggml-cuda/conv-transpose-1d.cuh"

 #include <algorithm>
 #include <array>
@ -2262,6 +2263,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
        case GGML_OP_IM2COL:
            ggml_cuda_op_im2col(ctx, dst);
            break;
+        case GGML_OP_CONV_TRANSPOSE_1D:
+            ggml_cuda_op_conv_transpose_1d(ctx,dst);
+            break;
        case GGML_OP_POOL_2D:
            ggml_cuda_op_pool2d(ctx, dst);
            break;
@ -2805,6 +2809,15 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
                ggml_type src0_type = op->src[0]->type;
                return src0_type != GGML_TYPE_I32 && src0_type != GGML_TYPE_I16;
            } break;
+        case GGML_OP_CONV_TRANSPOSE_1D:
+            {
+                ggml_type src0_type = op->src[0]->type;
+                ggml_type src1_type = op->src[1]->type;
+                if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) {
+                    return true;
+                }
+                return false;
+            } break;
        case GGML_OP_NONE:
        case GGML_OP_RESHAPE:
        case GGML_OP_VIEW:
--- a/ggml/src/ggml-cuda/conv-transpose-1d.cu
+++ b/ggml/src/ggml-cuda/conv-transpose-1d.cu
@ -0,0 +1,87 @@
+#include "conv-transpose-1d.cuh"
+
+static  __global__ void conv_transpose_1d_kernel(
+        const int s0, const int p0, const int d0, const int output_size,
+        const int src0_ne0, const int src0_ne1, const int src0_ne2, const int src0_ne3,
+        const int src1_ne0, const int src1_ne1, const int src1_ne2, const int src1_ne3,
+        const int dst_ne0, const int dst_ne1, const int dst_ne2, const int dst_ne3,
+        const float * src0, const float * src1,  float * dst) {
+    int global_index = threadIdx.x + blockIdx.x * blockDim.x;
+    if (global_index >= output_size) {
+        return;
+    }
+
+    int out_index = global_index / dst_ne0;
+
+    float accumulator = 0;
+
+    for (int c = 0; c < src0_ne2; c++) {
+        int idx = global_index % dst_ne0;
+
+        int kernel_offset = (src0_ne0 * src0_ne1 * c) + (out_index * src0_ne0);
+        int input_offset = src1_ne0 * c;
+
+        for (int i = 0; i < src1_ne0; i++) {
+            if (!(idx >= i*s0 && idx < i*s0 + src0_ne0)) {
+                continue;
+            }
+            int weight_idx = idx - i*s0;
+
+            float kernel_weight = src0[kernel_offset + weight_idx];
+            float input_value =  src1[input_offset+i];
+
+            accumulator += kernel_weight * input_value;
+        }
+    }
+    dst[global_index] = accumulator;
+}
+
+static void conv_transpose_1d_f32_f32_cuda(
+        const int s0, const int p0, const int d0, const int output_size,
+        const int src0_ne0, const int src0_ne1, const int src0_ne2, const int src0_ne3,
+        const int src1_ne0, const int src1_ne1, const int src1_ne2, const int src1_ne3,
+        const int dst_ne0, const int dst_ne1, const int dst_ne2, const int dst_ne3,
+        const float * src0, const float * src1,  float * dst,
+        cudaStream_t stream) {
+
+    const int num_blocks = (output_size + CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE - 1) / CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE;
+    conv_transpose_1d_kernel<<<num_blocks,CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE, 0, stream>>>(
+        s0,p0,d0,output_size,
+        src0_ne0, src0_ne1,  src0_ne2, src0_ne3,
+        src1_ne0, src1_ne1,  src1_ne2, src1_ne3,
+        dst_ne0,  dst_ne1,   dst_ne2,  dst_ne3,
+        src0,src1, dst);
+}
+
+void ggml_cuda_op_conv_transpose_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * src0 = dst->src[0];
+    const float * src0_d = (const float *)src0->data;
+
+    const ggml_tensor * src1 = dst->src[1];
+    const float * src1_d = (const float *)src1->data;
+
+    float * dst_d = (float *)dst->data;
+    cudaStream_t stream = ctx.stream();
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32);
+    GGML_ASSERT( dst->type == GGML_TYPE_F32);
+
+    GGML_ASSERT(ggml_is_contiguous(src0));
+    GGML_ASSERT(ggml_is_contiguous(src1));
+
+    const int32_t * opts = (const int32_t *)dst->op_params;
+
+    const int s0 = opts[0];
+    const int p0 = 0;//opts[3];
+    const int d0 = 1;//opts[4];
+
+    const int64_t kernel_size = ggml_nelements(src0);
+    const int64_t input_size = ggml_nelements(src1);
+    const int64_t output_size = ggml_nelements(dst);
+
+    conv_transpose_1d_f32_f32_cuda(s0, p0, d0, output_size,
+        src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3],
+        src1->ne[0], src1->ne[1], src1->ne[2], src1->ne[3],
+        dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
+        src0_d, src1_d, dst_d, stream);
+}
--- a/ggml/src/ggml-cuda/conv-transpose-1d.cuh
+++ b/ggml/src/ggml-cuda/conv-transpose-1d.cuh
@ -0,0 +1,5 @@
+#include "common.cuh"
+
+#define CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE 256
+
+void ggml_cuda_op_conv_transpose_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
--- a/ggml/src/ggml-impl.h
+++ b/ggml/src/ggml-impl.h
@ -609,6 +609,10 @@ static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {

 #endif // defined(__ARM_NEON) && (!defined(__MSC_VER)

+#ifdef __ARM_FEATURE_SVE
+#include <arm_sve.h>
+#endif // __ARM_FEATURE_SVE
+
 // precomputed f32 table for f16 (256 KB)
 // defined in ggml.c, initialized in ggml_init()
 extern float ggml_table_f32_f16[1 << 16];
--- a/ggml/src/ggml-quants.c
+++ b/ggml/src/ggml-quants.c
@ -3814,43 +3814,47 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, size_t bs, const void * r
    }
 #endif
 #if defined(__ARM_FEATURE_SVE)
-    const svbool_t ptrueh = svptrue_pat_b8(SV_VL16);
-    const svbool_t ptruel = svnot_b_z(svptrue_b8(), ptrueh);
+    if (svcntb() == QK8_0) {
+        const svbool_t ptrueh = svptrue_pat_b8(SV_VL16);
+        const svbool_t ptruel = svnot_b_z(svptrue_b8(), ptrueh);

-    svfloat32_t sumv0 = svdup_n_f32(0.0f);
-    svfloat32_t sumv1 = svdup_n_f32(0.0f);
+        svfloat32_t sumv0 = svdup_n_f32(0.0f);
+        svfloat32_t sumv1 = svdup_n_f32(0.0f);

-    assert(nb % 2 == 0); // TODO: handle odd nb
+        assert(nb % 2 == 0); // TODO: handle odd nb

-    for (int i = 0; i < nb; i += 2) {
-        const block_q4_0 * restrict x0 = &x[i + 0];
-        const block_q4_0 * restrict x1 = &x[i + 1];
-        const block_q8_0 * restrict y0 = &y[i + 0];
-        const block_q8_0 * restrict y1 = &y[i + 1];
+        for (int i = 0; i < nb; i += 2) {
+            const block_q4_0 * restrict x0 = &x[i + 0];
+            const block_q4_0 * restrict x1 = &x[i + 1];
+            const block_q8_0 * restrict y0 = &y[i + 0];
+            const block_q8_0 * restrict y1 = &y[i + 1];

-        // load x
-        const svuint8_t qx0r = svld1rq_u8(svptrue_b8(), x0->qs);
-        const svuint8_t qx1r = svld1rq_u8(svptrue_b8(), x1->qs);
+            // load x
+            const svuint8_t qx0r = svld1rq_u8(svptrue_b8(), x0->qs);
+            const svuint8_t qx1r = svld1rq_u8(svptrue_b8(), x1->qs);

-        // 4-bit -> 8-bit
-        const svint8_t qx0 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx0r, 0x0F), 0x04));
-        const svint8_t qx1 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx1r, 0x0F), 0x04));
+            // 4-bit -> 8-bit
+            const svint8_t qx0 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx0r, 0x0F), 0x04));
+            const svint8_t qx1 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx1r, 0x0F), 0x04));

-        // sub 8
-        const svint8_t qx0s = svsub_n_s8_x(svptrue_b8(), qx0, 8);
-        const svint8_t qx1s = svsub_n_s8_x(svptrue_b8(), qx1, 8);
+            // sub 8
+            const svint8_t qx0s = svsub_n_s8_x(svptrue_b8(), qx0, 8);
+            const svint8_t qx1s = svsub_n_s8_x(svptrue_b8(), qx1, 8);

-        // load y
-        const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
-        const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
+            // load y
+            const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
+            const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);

-        // dot product
-        sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
-        sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
+            // dot product
+            sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
+            sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
+        }
+
+        *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
+        return;
    }
-
-    *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
-#elif defined(__ARM_NEON)
+#endif
+#if defined(__ARM_NEON)
    float32x4_t sumv0 = vdupq_n_f32(0.0f);
    float32x4_t sumv1 = vdupq_n_f32(0.0f);

@ -5422,31 +5426,35 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * r
    }
 #endif
 #if defined(__ARM_FEATURE_SVE)
-    svfloat32_t sumv0 = svdup_n_f32(0.0f);
-    svfloat32_t sumv1 = svdup_n_f32(0.0f);
+    if (svcntb() == QK8_0) {
+        svfloat32_t sumv0 = svdup_n_f32(0.0f);
+        svfloat32_t sumv1 = svdup_n_f32(0.0f);

-    assert(nb % 2 == 0); // TODO: handle odd nb
+        assert(nb % 2 == 0); // TODO: handle odd nb

-    for (int i = 0; i < nb; i += 2) {
-        const block_q8_0 * restrict x0 = &x[i + 0];
-        const block_q8_0 * restrict x1 = &x[i + 1];
-        const block_q8_0 * restrict y0 = &y[i + 0];
-        const block_q8_0 * restrict y1 = &y[i + 1];
+        for (int i = 0; i < nb; i += 2) {
+            const block_q8_0 * restrict x0 = &x[i + 0];
+            const block_q8_0 * restrict x1 = &x[i + 1];
+            const block_q8_0 * restrict y0 = &y[i + 0];
+            const block_q8_0 * restrict y1 = &y[i + 1];

-        // load x
-        const svint8_t qx0 = svld1_s8(svptrue_b8(), x0->qs);
-        const svint8_t qx1 = svld1_s8(svptrue_b8(), x1->qs);
+            // load x
+            const svint8_t qx0 = svld1_s8(svptrue_b8(), x0->qs);
+            const svint8_t qx1 = svld1_s8(svptrue_b8(), x1->qs);

-        // load y
-        const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
-        const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
+            // load y
+            const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
+            const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);

-        sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
-        sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
+            sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
+            sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
+        }
+
+        *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
+        return;
    }
-
-    *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
-#elif defined(__ARM_NEON)
+#endif
+#if defined(__ARM_NEON)
    float32x4_t sumv0 = vdupq_n_f32(0.0f);
    float32x4_t sumv1 = vdupq_n_f32(0.0f);

@ -14760,6 +14768,16 @@ static bool validate_fp16(ggml_fp16_t f, size_t i) {
        } \
    }

+#define VALIDATE_ROW_DATA_DVEC_F16_IMPL(type, data, nb, nr) \
+    const type * q = (const type *) (data); \
+    for (size_t i = 0; i < (nb); ++i) { \
+        for (size_t j = 0; j < (nr); ++j) { \
+            if (!validate_fp16(q[i].d[j], i)) { \
+                return false; \
+            } \
+        } \
+    }
+
 bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbytes) {
    if (type < 0 || type >= GGML_TYPE_COUNT) {
        fprintf(stderr, "%s: invalid type %d\n", __func__, type);
@ -14977,6 +14995,16 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
            {
                VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_nl, data, nb);
            } break;
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+            {
+                VALIDATE_ROW_DATA_DVEC_F16_IMPL(block_q4_0x4, data, nbytes / sizeof(block_q4_0x4), 4);
+            } break;
+        case GGML_TYPE_Q4_0_8_8:
+            {
+                VALIDATE_ROW_DATA_DVEC_F16_IMPL(block_q4_0x8, data, nbytes / sizeof(block_q4_0x8), 8);
+            } break;
+
        case GGML_TYPE_I8:
        case GGML_TYPE_I16:
        case GGML_TYPE_I32:
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@ -3658,6 +3658,10 @@ static void ggml_sycl_mul_mat(ggml_backend_sycl_context & ctx, const ggml_tensor
    use_mul_mat_q = use_mul_mat_q && (src1->ne[1] <= MMQ_MAX_BATCH_SIZE);
 #endif // SYCL_USE_XMX

+    // mmvq path is faster in the CUDA backend.
+    if (ctx.stream()->get_backend() == sycl::backend::ext_oneapi_cuda)
+        use_dequantize_mul_mat_vec = use_dequantize_mul_mat_vec && !use_mul_mat_vec_q;
+
    if (!split && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) {
        // KQ single-batch
        ggml_sycl_mul_mat_vec_p021(ctx, src0, src1, dst);
--- a/ggml/src/ggml-sycl/common.hpp
+++ b/ggml/src/ggml-sycl/common.hpp
@ -346,4 +346,10 @@ inline sycl::vec<Tp, n> vec_aligned_load(const Tp* aligned_ptr) {
    return *reinterpret_cast<const sycl::vec<Tp, n>*>(aligned_ptr);
 }

+// Helper for accessing pointers with no warnings
+template <typename Tp, int dim>
+static __dpct_inline__ Tp* get_pointer(sycl::local_accessor<Tp, dim> acc) {
+    return acc.template get_multi_ptr<sycl::access::decorated::no>().get();
+}
+
 #endif // GGML_SYCL_COMMON_HPP
--- a/ggml/src/ggml-sycl/convert.cpp
+++ b/ggml/src/ggml-sycl/convert.cpp
@ -158,7 +158,7 @@ static void dequantize_row_q4_K_sycl(const void *vx, dst_t *y, const int k,
                                                   sycl::range<3>(1, 1, 32),
                                               sycl::range<3>(1, 1, 32)),
                             [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q4_K(vx, y, scale_local_acc.get_pointer(), item_ct1);
+                                 dequantize_block_q4_K(vx, y, get_pointer(scale_local_acc), item_ct1);
                             });
        });
    }
--- a/ggml/src/ggml-sycl/mmq.cpp
+++ b/ggml/src/ggml-sycl/mmq.cpp
@ -1835,10 +1835,10 @@ static void ggml_mul_mat_q4_0_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q4_0<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_qs_q4_0_acc_ct1.get_pointer(),
-                            tile_x_d_q4_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_0_acc_ct1),
+                            get_pointer(tile_x_d_q4_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -1870,10 +1870,10 @@ static void ggml_mul_mat_q4_0_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q4_0<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_qs_q4_0_acc_ct1.get_pointer(),
-                            tile_x_d_q4_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_0_acc_ct1),
+                            get_pointer(tile_x_d_q4_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -1950,10 +1950,10 @@ static void ggml_mul_mat_q4_1_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q4_1<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_qs_q4_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_1_acc_ct1),
+                            get_pointer(tile_x_dm_q4_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -1985,10 +1985,10 @@ static void ggml_mul_mat_q4_1_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q4_1<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_qs_q4_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_1_acc_ct1),
+                            get_pointer(tile_x_dm_q4_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2065,10 +2065,10 @@ static void ggml_mul_mat_q5_0_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q5_0<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q5_0_acc_ct1.get_pointer(),
-                            tile_x_d_q5_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_0_acc_ct1),
+                            get_pointer(tile_x_d_q5_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2100,10 +2100,10 @@ static void ggml_mul_mat_q5_0_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q5_0<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q5_0_acc_ct1.get_pointer(),
-                            tile_x_d_q5_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_0_acc_ct1),
+                            get_pointer(tile_x_d_q5_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2180,10 +2180,10 @@ static void ggml_mul_mat_q5_1_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q5_1<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q5_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_1_acc_ct1),
+                            get_pointer(tile_x_dm_q5_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2215,10 +2215,10 @@ static void ggml_mul_mat_q5_1_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q5_1<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q5_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_1_acc_ct1),
+                            get_pointer(tile_x_dm_q5_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2295,10 +2295,10 @@ static void ggml_mul_mat_q8_0_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q8_0<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_qs_q8_0_acc_ct1.get_pointer(),
-                            tile_x_d_q8_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q8_0_acc_ct1),
+                            get_pointer(tile_x_d_q8_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2330,10 +2330,10 @@ static void ggml_mul_mat_q8_0_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q8_0<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_qs_q8_0_acc_ct1.get_pointer(),
-                            tile_x_d_q8_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q8_0_acc_ct1),
+                            get_pointer(tile_x_d_q8_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2412,11 +2412,11 @@ static void ggml_mul_mat_q2_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q2_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q2_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q2_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q2_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q2_K_acc_ct1),
+                            get_pointer(tile_x_dm_q2_K_acc_ct1),
+                            get_pointer(tile_x_sc_q2_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2450,11 +2450,11 @@ static void ggml_mul_mat_q2_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q2_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q2_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q2_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q2_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q2_K_acc_ct1),
+                            get_pointer(tile_x_dm_q2_K_acc_ct1),
+                            get_pointer(tile_x_sc_q2_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2537,12 +2537,12 @@ static void ggml_mul_mat_q3_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q3_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q3_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q3_K_acc_ct1.get_pointer(),
-                            tile_x_qh_q3_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q3_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q3_K_acc_ct1),
+                            get_pointer(tile_x_dm_q3_K_acc_ct1),
+                            get_pointer(tile_x_qh_q3_K_acc_ct1),
+                            get_pointer(tile_x_sc_q3_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2578,12 +2578,12 @@ static void ggml_mul_mat_q3_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q3_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q3_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q3_K_acc_ct1.get_pointer(),
-                            tile_x_qh_q3_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q3_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q3_K_acc_ct1),
+                            get_pointer(tile_x_dm_q3_K_acc_ct1),
+                            get_pointer(tile_x_qh_q3_K_acc_ct1),
+                            get_pointer(tile_x_sc_q3_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2663,11 +2663,11 @@ static void ggml_mul_mat_q4_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q4_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q4_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q4_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q4_K_acc_ct1),
+                            get_pointer(tile_x_dm_q4_K_acc_ct1),
+                            get_pointer(tile_x_sc_q4_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2701,11 +2701,11 @@ static void ggml_mul_mat_q4_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q4_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q4_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q4_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q4_K_acc_ct1),
+                            get_pointer(tile_x_dm_q4_K_acc_ct1),
+                            get_pointer(tile_x_sc_q4_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2784,11 +2784,11 @@ static void ggml_mul_mat_q5_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q5_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q5_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q5_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_K_acc_ct1),
+                            get_pointer(tile_x_dm_q5_K_acc_ct1),
+                            get_pointer(tile_x_sc_q5_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2822,11 +2822,11 @@ static void ggml_mul_mat_q5_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q5_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_q5_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q5_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_K_acc_ct1),
+                            get_pointer(tile_x_dm_q5_K_acc_ct1),
+                            get_pointer(tile_x_sc_q5_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2905,11 +2905,11 @@ static void ggml_mul_mat_q6_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q6_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_acc_ct1.get_pointer(),
-                            tile_x_dm_acc_ct1.get_pointer(),
-                            tile_x_sc_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_acc_ct1),
+                            get_pointer(tile_x_dm_acc_ct1),
+                            get_pointer(tile_x_sc_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
@ -2943,11 +2943,11 @@ static void ggml_mul_mat_q6_K_q8_1_sycl(const void *vx, const void *vy,
                        mul_mat_q6_K<need_check>(
                            vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                            nrows_dst, item_ct1,
-                            tile_x_ql_acc_ct1.get_pointer(),
-                            tile_x_dm_acc_ct1.get_pointer(),
-                            tile_x_sc_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_acc_ct1),
+                            get_pointer(tile_x_dm_acc_ct1),
+                            get_pointer(tile_x_sc_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                    });
            });
        }
--- a/ggml/src/ggml-sycl/norm.cpp
+++ b/ggml/src/ggml-sycl/norm.cpp
@ -218,7 +218,7 @@ static void norm_f32_sycl(const float* x, float* dst, const int ncols,
                [=](sycl::nd_item<3> item_ct1)
                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                    norm_f32(x, dst, ncols, eps, item_ct1,
-                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                        get_pointer(s_sum_acc_ct1), work_group_size);
                });
            });
    }
@ -265,7 +265,7 @@ static void group_norm_f32_sycl(const float* x, float* dst,
                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                    group_norm_f32(x, dst, group_size, ne_elements,
                        eps_ct4, item_ct1,
-                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                        get_pointer(s_sum_acc_ct1), work_group_size);
                });
            });
    }
@ -306,7 +306,7 @@ static void rms_norm_f32_sycl(const float* x, float* dst, const int ncols,
                [=](sycl::nd_item<3> item_ct1)
                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                    rms_norm_f32(x, dst, ncols, eps, item_ct1,
-                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                        get_pointer(s_sum_acc_ct1), work_group_size);
                });
            });
    }
--- a/ggml/src/ggml-sycl/rope.cpp
+++ b/ggml/src/ggml-sycl/rope.cpp
@ -55,7 +55,7 @@ static void rope_norm(
    const int i = row*ne0 + i0;
    const int i2 = row/p_delta_rows;

-    const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
+    const float theta_base = pos[i2] * sycl::pow(theta_scale, i0 / 2.0f);

    const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;

@ -98,7 +98,7 @@ static void rope_neox(
    const int i  = row*ne0 + i0/2;
    const int i2 = row/p_delta_rows;

-    const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
+    const float theta_base = pos[i2] * sycl::pow(theta_scale, i0 / 2.0f);

    const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;

--- a/ggml/src/ggml-sycl/softmax.cpp
+++ b/ggml/src/ggml-sycl/softmax.cpp
@ -136,7 +136,7 @@ static void soft_max_f32_submitter(const float * x, const float * mask, float *
                soft_max_f32<vals_smem, ncols_template, block_size_template>(x, mask, dst, ncols_par,
                                                                             nrows_y, scale, max_bias, m0,
                                                                             m1, n_head_log2, item_ct1,
-                                                                             local_buf_acc.get_pointer());
+                                                                             get_pointer(local_buf_acc));
            });
    });
 }
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@ -4,7 +4,7 @@
 #include "ggml-impl.h"
 #include "ggml-quants.h"
 #include "ggml.h"
-
+#include "ggml-aarch64.h"

 #if defined(_MSC_VER) || defined(__MINGW32__)
 #include <malloc.h> // using malloc.h with MSC/MINGW
@ -37,12 +37,12 @@
 #include <unistd.h>
 #endif

-#ifdef __ARM_FEATURE_MATMUL_INT8
+#if defined(__ARM_FEATURE_SVE) || defined(__ARM_FEATURE_MATMUL_INT8)
 #undef GGML_USE_LLAMAFILE
 #endif

 #ifdef GGML_USE_LLAMAFILE
-#include "sgemm.h"
+#include <llamafile/sgemm.h>
 #endif

 #if defined(_MSC_VER)
@ -692,6 +692,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
 #else
        .nrows                    = 1,
 #endif
+        .from_float_to_mat        = quantize_mat_q8_0,
    },
    [GGML_TYPE_Q8_1] = {
        .type_name                = "q8_1",
@ -889,6 +890,54 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
        .vec_dot                  = (ggml_vec_dot_t) ggml_vec_dot_bf16,
        .vec_dot_type             = GGML_TYPE_BF16,
        .nrows                    = 1,
+    },
+    [GGML_TYPE_Q4_0_4_4] = {
+        .type_name                = "q4_0_4x4",
+        .blck_size                = QK4_0,
+        .type_size                = sizeof(block_q4_0),
+        .is_quantized             = true,
+        .to_float                 = NULL,
+        .from_float               = NULL,
+        .from_float_reference     = NULL,
+        .vec_dot                  = NULL,
+        .vec_dot_type             = GGML_TYPE_Q8_0,
+        .nrows                    = 1,
+        .ncols                    = 4,
+        .interleave_blcksize      = 4,
+        .gemv                     = ggml_gemv_q4_0_4x4_q8_0,
+        .gemm                     = ggml_gemm_q4_0_4x4_q8_0,
+    },
+    [GGML_TYPE_Q4_0_4_8] = {
+        .type_name                = "q4_0_4x8",
+        .blck_size                = QK4_0,
+        .type_size                = sizeof(block_q4_0),
+        .is_quantized             = true,
+        .to_float                 = NULL,
+        .from_float               = NULL,
+        .from_float_reference     = NULL,
+        .vec_dot                  = NULL,
+        .vec_dot_type             = GGML_TYPE_Q8_0,
+        .nrows                    = 1,
+        .ncols                    = 4,
+        .interleave_blcksize      = 8,
+        .gemv                     = ggml_gemv_q4_0_4x8_q8_0,
+        .gemm                     = ggml_gemm_q4_0_4x8_q8_0,
+    },
+    [GGML_TYPE_Q4_0_8_8] = {
+        .type_name                = "q4_0_8x8",
+        .blck_size                = QK4_0,
+        .type_size                = sizeof(block_q4_0),
+        .is_quantized             = true,
+        .to_float                 = NULL,
+        .from_float               = NULL,
+        .from_float_reference     = NULL,
+        .vec_dot                  = NULL,
+        .vec_dot_type             = GGML_TYPE_Q8_0,
+        .nrows                    = 1,
+        .ncols                    = 8,
+        .interleave_blcksize      = 8,
+        .gemv                     = ggml_gemv_q4_0_8x8_q8_0,
+        .gemm                     = ggml_gemm_q4_0_8x8_q8_0,
    }
 };

@ -3188,6 +3237,9 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
        case GGML_FTYPE_MOSTLY_IQ4_XS:        wtype = GGML_TYPE_IQ4_XS;   break;
        case GGML_FTYPE_MOSTLY_IQ3_S:         wtype = GGML_TYPE_IQ3_S;    break;
        case GGML_FTYPE_MOSTLY_IQ2_S:         wtype = GGML_TYPE_IQ2_S;    break;
+        case GGML_FTYPE_MOSTLY_Q4_0_4_4:      wtype = GGML_TYPE_Q4_0_4_4; break;
+        case GGML_FTYPE_MOSTLY_Q4_0_4_8:      wtype = GGML_TYPE_Q4_0_4_8; break;
+        case GGML_FTYPE_MOSTLY_Q4_0_8_8:      wtype = GGML_TYPE_Q4_0_8_8; break;
        case GGML_FTYPE_UNKNOWN:              wtype = GGML_TYPE_COUNT; break;
        case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16: wtype = GGML_TYPE_COUNT; break;
    }
@ -9432,6 +9484,9 @@ static void ggml_compute_forward_add(
        case GGML_TYPE_IQ4_XS:
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
            {
                ggml_compute_forward_add_q_f32(params, dst);
            } break;
@ -9807,6 +9862,9 @@ static void ggml_compute_forward_add1(
        case GGML_TYPE_IQ4_XS:
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
            {
                ggml_compute_forward_add1_q_f32(params, dst);
            } break;
@ -9932,6 +9990,9 @@ static void ggml_compute_forward_acc(
        case GGML_TYPE_IQ4_XS:
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
        default:
            {
                GGML_ASSERT(false);
@ -12134,6 +12195,12 @@ static void ggml_compute_forward_mul_mat(
    enum ggml_type    const vec_dot_type          = type_traits[type].vec_dot_type;
    ggml_from_float_t const from_float_to_vec_dot = type_traits[vec_dot_type].from_float;
    int64_t           const vec_dot_num_rows      = type_traits[type].nrows;
+    int64_t           const matmul_num_cols       = type_traits[type].ncols;
+    int64_t           const interleave_blcksize   = type_traits[type].interleave_blcksize;
+    ggml_from_float_to_mat_t const from_float_to_mat
+                                                  = type_traits[vec_dot_type].from_float_to_mat;
+    ggml_gemv_t       const gemv                  = type_traits[type].gemv;
+    ggml_gemm_t       const gemm                  = type_traits[type].gemm;

    GGML_ASSERT(ne0 == ne01);
    GGML_ASSERT(ne1 == ne11);
@ -12192,7 +12259,16 @@ UseGgmlGemm1:;

        for (int64_t i13 = 0; i13 < ne13; ++i13) {
            for (int64_t i12 = 0; i12 < ne12; ++i12) {
-                for (int64_t i11 = ith; i11 < ne11; i11 += nth) {
+                int64_t i11_processed = 0;
+                if ((ggml_n_dims(src1) == 2) && from_float_to_mat && gemm) {
+                    for (int64_t i11 = ith * 4; i11 < ne11 - ne11 % 4; i11 += nth * 4) {
+                        from_float_to_mat((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
+                                          (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
+                                          4, ne10, interleave_blcksize);
+                    }
+                    i11_processed = ne11 - ne11 % 4;
+                }
+                for (int64_t i11 = i11_processed + ith; i11 < ne11; i11 += nth) {
                    from_float_to_vec_dot((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
                                          (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
                                           ne10);
@ -12273,6 +12349,28 @@ UseGgmlGemm2:;
    const int64_t dr0 = (nr0 + nchunk0 - 1) / nchunk0;
    const int64_t dr1 = (nr1 + nchunk1 - 1) / nchunk1;

+    if ((ggml_n_dims(src0) == 2) && gemv) {
+        const void * src1_wdata      = (src1->type == vec_dot_type) ? src1->data : params->wdata;
+        const size_t src1_col_stride = ggml_is_contiguous(src1) || src1->type != vec_dot_type ? ggml_row_size(vec_dot_type, ne10) : nb11;
+        int64_t src0_start = (ith * ne01) / nth;
+        int64_t src0_end   = ((ith + 1) * ne01) / nth;
+        src0_start = (src0_start % matmul_num_cols) ? src0_start + matmul_num_cols - (src0_start % matmul_num_cols): src0_start;
+        src0_end   = (src0_end % matmul_num_cols) ? src0_end + matmul_num_cols - (src0_end % matmul_num_cols): src0_end;
+        if (src0_start >= src0_end) return;
+
+        // If there are more than three rows in src1, use gemm; otherwise, use gemv.
+        if (gemm && (ne11 > 3)) {
+            gemm(ne00, (float *)((char *) dst->data) + src0_start, ne01, (const char *) src0->data + src0_start * nb01,
+                 (const char *) src1_wdata, ne11 - ne11 % 4, src0_end - src0_start);
+        }
+        for (int iter = gemm ? ne11 - ne11 % 4 : 0; iter < ne11; iter++) {
+            gemv(ne00, (float *)((char *) dst->data + (iter * nb1)) + src0_start, ne01,
+                 (const char *) src0->data + src0_start * nb01, (const char *) src1_wdata + (src1_col_stride * iter), 1,
+                 src0_end - src0_start);
+        }
+        return;
+    }
+
    // The first chunk comes from our thread_id, the rest will get auto-assigned.
    int current_chunk = ith;

@ -12318,6 +12416,8 @@ static void ggml_compute_forward_mul_mat_id(
    ggml_vec_dot_t    const vec_dot               = type_traits[type].vec_dot;
    enum ggml_type    const vec_dot_type          = type_traits[type].vec_dot_type;
    ggml_from_float_t const from_float_to_vec_dot = type_traits[vec_dot_type].from_float;
+    int64_t           const matmul_num_cols       = type_traits[type].ncols;
+    ggml_gemv_t       const gemv                  = type_traits[type].gemv;

    // we don't support permuted src0 or src1
    GGML_ASSERT(nb00 == ggml_type_size(type));
@ -12403,6 +12503,34 @@ static void ggml_compute_forward_mul_mat_id(
        const int64_t nr0 = ne01; // src0 rows
        const int64_t nr1 = cne1; // src1 rows

+        if (((ggml_n_dims(src0) - 1) == 2) && gemv) {
+            int64_t src0_cur_start = (ith * ne01) / nth;
+            int64_t src0_cur_end   = ((ith + 1) * ne01) / nth;
+            src0_cur_start = (src0_cur_start % matmul_num_cols) ? src0_cur_start + matmul_num_cols - (src0_cur_start % matmul_num_cols): src0_cur_start;
+            src0_cur_end   = (src0_cur_end % matmul_num_cols) ? src0_cur_end + matmul_num_cols - (src0_cur_end % matmul_num_cols): src0_cur_end;
+            if (src0_cur_start >= src0_cur_end) return;
+
+            for (int ir1 = 0; ir1 < nr1; ir1++) {
+                struct mmid_row_mapping row_mapping = MMID_MATRIX_ROW(cur_a, ir1);
+                const int id       = row_mapping.i1; // selected expert index
+
+                const int64_t  i11 = id % ne11;
+                const int64_t  i12 = row_mapping.i2; // row index in src1
+
+                const int64_t  i1 = id;  // selected expert index
+                const int64_t  i2 = i12; // row
+
+                const char * src1_col = (const char *) wdata +
+                    (src1_cont || src1->type != vec_dot_type
+                    ? (i11        + i12 * ne11) * row_size
+                    : (i11 * nb11 + i12 * nb12));
+
+                gemv(ne00, (float *)((char *) dst->data + (i1 * nb1 + i2 * nb2)) + src0_cur_start, ne01,
+                     (const char *) src0_cur + src0_cur_start * nb01, src1_col, 1, src0_cur_end - src0_cur_start);
+            }
+            continue;
+        }
+
        // distribute the thread work across the inner or outer loop based on which one is larger

        const int64_t nth0 = nr0 > nr1 ? nth : 1; // parallelize by src0 rows
@ -12704,6 +12832,9 @@ static void ggml_compute_forward_out_prod(
        case GGML_TYPE_IQ4_XS:
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
            {
                ggml_compute_forward_out_prod_q_f32(params, dst);
            } break;
@ -12889,6 +13020,9 @@ static void ggml_compute_forward_set(
        case GGML_TYPE_IQ4_XS:
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
        default:
            {
                GGML_ASSERT(false);
@ -13148,6 +13282,9 @@ static void ggml_compute_forward_get_rows(
        case GGML_TYPE_IQ4_XS:
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
            {
                ggml_compute_forward_get_rows_q(params, dst);
            } break;
@ -13734,6 +13871,9 @@ static void ggml_compute_forward_clamp(
        case GGML_TYPE_IQ3_S:
        case GGML_TYPE_IQ2_S:
        case GGML_TYPE_Q8_K:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
        case GGML_TYPE_I8:
        case GGML_TYPE_I16:
        case GGML_TYPE_I32:
@ -20457,6 +20597,9 @@ size_t ggml_quantize_chunk(
        case GGML_TYPE_IQ1_M:   result = quantize_iq1_m  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
        case GGML_TYPE_IQ4_NL:  result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
        case GGML_TYPE_IQ4_XS:  result = quantize_iq4_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_0_4_4: result = quantize_q4_0_4x4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_0_4_8: result = quantize_q4_0_4x8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_0_8_8: result = quantize_q4_0_8x8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
        case GGML_TYPE_F16:
            {
                size_t elemsize = sizeof(ggml_fp16_t);
@ -21759,8 +21902,6 @@ int ggml_cpu_has_neon(void) {

 int ggml_cpu_has_sve(void) {
 #if defined(__ARM_FEATURE_SVE)
-    // TODO: Currently, SVE 256 bit is only supported.
-    GGML_ASSERT(svcntb() == QK8_0);
    return 1;
 #else
    return 0;
--- a/ggml/src/llamafile/sgemm.cpp
+++ b/ggml/src/llamafile/sgemm.cpp
--- a/ggml/src/llamafile/sgemm.h
+++ b/ggml/src/llamafile/sgemm.h
--- a/gguf-py/README.md
+++ b/gguf-py/README.md
@ -79,5 +79,4 @@ python -m twine upload dist/*
 ```

 ## TODO
- [ ] Add tests
 - [ ] Include conversion scripts as command line entry points in this package.
--- a/gguf-py/gguf/gguf_reader.py
+++ b/gguf-py/gguf/gguf_reader.py
@ -67,7 +67,7 @@ class ReaderTensor(NamedTuple):

 class GGUFReader:
    # I - same as host, S - swapped
-    byte_order: Literal['I'] | Literal['S'] = 'I'
+    byte_order: Literal['I', 'S'] = 'I'
    alignment: int = GGUF_DEFAULT_ALIGNMENT
    data_offset: int

@ -86,7 +86,7 @@ class GGUFReader:
        GGUFValueType.BOOL:    np.bool_,
    }

-    def __init__(self, path: os.PathLike[str] | str, mode: Literal['r'] | Literal['r+'] | Literal['c'] = 'r'):
+    def __init__(self, path: os.PathLike[str] | str, mode: Literal['r', 'r+', 'c'] = 'r'):
        self.data = np.memmap(path, mode = mode)
        offs = 0

@ -140,7 +140,7 @@ class GGUFReader:
        return self.tensors[idx]

    def _get(
-        self, offset: int, dtype: npt.DTypeLike, count: int = 1, override_order: None | Literal['I'] | Literal['S'] | Literal['<'] = None,
+        self, offset: int, dtype: npt.DTypeLike, count: int = 1, override_order: None | Literal['I', 'S', '<'] = None,
    ) -> npt.NDArray[Any]:
        count = int(count)
        itemsize = int(np.empty([], dtype = dtype).itemsize)
--- a/gguf-py/gguf/lazy.py
+++ b/gguf-py/gguf/lazy.py
@ -6,7 +6,6 @@ from typing import Any, Callable
 from collections import deque

 import numpy as np
-from numpy._typing import _Shape
 from numpy.typing import DTypeLike


@ -16,16 +15,16 @@ logger = logging.getLogger(__name__)
 class LazyMeta(ABCMeta):

    def __new__(cls, name: str, bases: tuple[type, ...], namespace: dict[str, Any], **kwargs):
-        def __getattr__(self, __name: str) -> Any:
-            meta_attr = getattr(self._meta, __name)
+        def __getattr__(self, name: str) -> Any:
+            meta_attr = getattr(self._meta, name)
            if callable(meta_attr):
                return type(self)._wrap_fn(
-                    (lambda s, *args, **kwargs: getattr(s, __name)(*args, **kwargs)),
+                    (lambda s, *args, **kwargs: getattr(s, name)(*args, **kwargs)),
                    use_self=self,
                )
            elif isinstance(meta_attr, self._tensor_type):
                # e.g. self.T with torch.Tensor should still be wrapped
-                return type(self)._wrap_fn(lambda s: getattr(s, __name))(self)
+                return type(self)._wrap_fn(lambda s: getattr(s, name))(self)
            else:
                # no need to wrap non-tensor properties,
                # and they likely don't depend on the actual contents of the tensor
@ -141,19 +140,21 @@ class LazyBase(ABC, metaclass=LazyMeta):
                        res = cls.meta_with_dtype_and_shape(meta_noop, res.shape)

            if isinstance(res, cls._tensor_type):
-                def collect_replace(t: LazyBase):
-                    if collect_replace.shared_lazy is None:
-                        collect_replace.shared_lazy = t._lazy
-                    else:
-                        collect_replace.shared_lazy.extend(t._lazy)
-                        t._lazy = collect_replace.shared_lazy
+                class CollectSharedLazy:
+                    # emulating a static variable
+                    shared_lazy: None | deque[LazyBase] = None

-                # emulating a static variable
-                collect_replace.shared_lazy = None
+                    @staticmethod
+                    def collect_replace(t: LazyBase):
+                        if CollectSharedLazy.shared_lazy is None:
+                            CollectSharedLazy.shared_lazy = t._lazy
+                        else:
+                            CollectSharedLazy.shared_lazy.extend(t._lazy)
+                            t._lazy = CollectSharedLazy.shared_lazy

-                LazyBase._recurse_apply(args, collect_replace)
+                LazyBase._recurse_apply(args, CollectSharedLazy.collect_replace)

-                shared_lazy = collect_replace.shared_lazy
+                shared_lazy = CollectSharedLazy.shared_lazy

                return cls(meta=cls.eager_to_meta(res), lazy=shared_lazy, args=args, func=lambda a: fn(*a, **kwargs))
            else:
@ -184,6 +185,7 @@ class LazyBase(ABC, metaclass=LazyMeta):
                lt._args = cls._recurse_apply(lt._args, already_eager_to_eager)
                lt._data = lt._func(lt._args)
                # sanity check
+                assert lt._data is not None
                assert lt._data.dtype == lt._meta.dtype
                assert lt._data.shape == lt._meta.shape

@ -216,7 +218,7 @@ class LazyNumpyTensor(LazyBase):
    _tensor_type = np.ndarray

    @classmethod
-    def meta_with_dtype_and_shape(cls, dtype: DTypeLike, shape: _Shape) -> np.ndarray[Any, Any]:
+    def meta_with_dtype_and_shape(cls, dtype: DTypeLike, shape: tuple[int, ...]) -> np.ndarray[Any, Any]:
        # The initial idea was to use np.nan as the fill value,
        # but non-float types like np.int16 can't use that.
        # So zero it is.
--- a/gguf-py/pyproject.toml
+++ b/gguf-py/pyproject.toml
@ -1,6 +1,6 @@
 [tool.poetry]
 name = "gguf"
-version = "0.9.0"
+version = "0.9.1"
 description = "Read and write ML models in GGUF for GGML"
 authors = ["GGML <ggml@ggml.ai>"]
 packages = [
--- a/gguf-py/scripts/init.py
+++ b/gguf-py/scripts/init.py
@ -1,3 +1,5 @@
+# pyright: reportUnusedImport=false
+
 from .gguf_convert_endian import main as gguf_convert_endian_entrypoint
 from .gguf_dump import main as gguf_dump_entrypoint
 from .gguf_set_metadata import main as gguf_set_metadata_entrypoint
--- a/gguf-py/scripts/gguf_hash.py
+++ b/gguf-py/scripts/gguf_hash.py
@ -63,9 +63,9 @@ def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar) -> None:
        bar.update(sum_weights_in_tensor)

        sha1_layer = hashlib.sha1()
-        sha1_layer.update(tensor.data)
-        sha1.update(tensor.data)
-        uuidv5_sha1.update(tensor.data)
+        sha1_layer.update(tensor.data.data)
+        sha1.update(tensor.data.data)
+        uuidv5_sha1.update(tensor.data.data)
        print("sha1    {0}  {1}:{2}".format(sha1_layer.hexdigest(), filename, tensor.name)) # noqa: NP100

    # Flush Hash Progress Bar
--- a/gguf-py/scripts/gguf_new_metadata.py
+++ b/gguf-py/scripts/gguf_new_metadata.py
@ -1,4 +1,6 @@
 #!/usr/bin/env python3
+from __future__ import annotations
+
 import logging
 import argparse
 import os
--- a/gguf-py/tests/test_gguf.py
+++ b/gguf-py/tests/test_gguf.py
@ -1,4 +1,4 @@
-import gguf  # noqa: F401
+import gguf  # noqa: F401  # pyright: ignore[reportUnusedImport]

 # TODO: add tests

--- a/grammars/README.md
+++ b/grammars/README.md
@ -4,7 +4,7 @@ GBNF (GGML BNF) is a format for defining [formal grammars](https://en.wikipedia.

 ## Background

-[Bakus-Naur Form (BNF)](https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form) is a notation for describing the syntax of formal languages like programming languages, file formats, and protocols. GBNF is an extension of BNF that primarily adds a few modern regex-like features.
+[Backus-Naur Form (BNF)](https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form) is a notation for describing the syntax of formal languages like programming languages, file formats, and protocols. GBNF is an extension of BNF that primarily adds a few modern regex-like features.

 ## Basics

--- a/include/llama.h
+++ b/include/llama.h
@ -162,6 +162,9 @@ extern "C" {
        LLAMA_FTYPE_MOSTLY_IQ4_XS        = 30, // except 1d tensors
        LLAMA_FTYPE_MOSTLY_IQ1_M         = 31, // except 1d tensors
        LLAMA_FTYPE_MOSTLY_BF16          = 32, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q4_0_4_4      = 33, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q4_0_4_8      = 34, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q4_0_8_8      = 35, // except 1d tensors

        LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
    };
--- a/pyrightconfig.json
+++ b/pyrightconfig.json
@ -1,3 +1,21 @@
 {
  "extraPaths": ["gguf-py"],
-}
+  "pythonVersion": "3.9",
+  "pythonPlatform": "All",
+  "reportUnusedImport": "warning",
+  "reportDuplicateImport": "error",
+  "reportDeprecated": "warning",
+  "reportUnnecessaryTypeIgnoreComment": "warning",
+  "executionEnvironments": [
+    {
+      // TODO: make this version override work correctly
+      "root": "gguf-py",
+      "pythonVersion": "3.8",
+    },
+    {
+      // uses match expressions in steps.py
+      "root": "examples/server/tests",
+      "pythonVersion": "3.10",
+    },
+  ],
+ }
--- a/requirements/requirements-all.txt
+++ b/requirements/requirements-all.txt
@ -0,0 +1,12 @@
+-r ../examples/llava/requirements.txt
+-r ../examples/server/bench/requirements.txt
+-r ../examples/server/tests/requirements.txt
+
+-r ./requirements-compare-llama-bench.txt
+-r ./requirements-pydantic.txt
+-r ./requirements-test-tokenizer-random.txt
+
+-r ./requirements-convert_hf_to_gguf.txt
+-r ./requirements-convert_hf_to_gguf_update.txt
+-r ./requirements-convert_legacy_llama.txt
+-r ./requirements-convert_llama_ggml_to_gguf.txt
--- a/requirements/requirements-compare-llama-bench.txt
+++ b/requirements/requirements-compare-llama-bench.txt
@ -0,0 +1,2 @@
+tabulate~=0.9.0
+GitPython~=3.1.43
--- a/requirements/requirements-pydantic.txt
+++ b/requirements/requirements-pydantic.txt
@ -0,0 +1,2 @@
+docstring_parser~=0.15
+pydantic~=2.6.3
--- a/requirements/requirements-test-tokenizer-random.txt
+++ b/requirements/requirements-test-tokenizer-random.txt
@ -0,0 +1 @@
+cffi~=1.16.0
--- a/scripts/check-requirements.sh
+++ b/scripts/check-requirements.sh
@ -108,6 +108,11 @@ check_convert_script() {
        fatal "$py missing requirements. Expected: $reqs"
    fi

+    # Check that all sub-requirements are added to top-level requirements.txt
+    if ! grep -qF "$reqs" requirements.txt; then
+        fatal "$reqs needs to be added to requirements.txt"
+    fi
+
    local venv="$workdir/$pyname-venv"
    python3 -m venv "$venv"

@ -134,12 +139,7 @@ EOF

 readonly ignore_eq_eq='check_requirements: ignore "=="'

-for req in "$reqs_dir"/*; do
-    # Check that all sub-requirements are added to top-level requirements.txt
-    if ! grep -qF "$req" requirements.txt; then
-        fatal "$req needs to be added to requirements.txt"
-    fi
-
+for req in */**/requirements*.txt; do
    # Make sure exact release versions aren't being pinned in the requirements
    # Filters out the ignore string
    if grep -vF "$ignore_eq_eq" "$req" | grep -q '=='; then
--- a/scripts/compare-llama-bench.py
+++ b/scripts/compare-llama-bench.py
@ -123,13 +123,13 @@ builds = cursor.execute("SELECT DISTINCT build_commit FROM test;").fetchall()

 try:
    repo = git.Repo(".", search_parent_directories=True)
-except git.exc.InvalidGitRepositoryError:
+except git.InvalidGitRepositoryError:
    repo = None


-def find_parent_in_data(commit):
+def find_parent_in_data(commit: git.Commit):
    """Helper function to find the most recent parent measured in number of commits for which there is data."""
-    heap = [(0, commit)]
+    heap: list[tuple[int, git.Commit]] = [(0, commit)]
    seen_hexsha8 = set()
    while heap:
        depth, current_commit = heapq.heappop(heap)
@ -144,7 +144,7 @@ def find_parent_in_data(commit):
    return None


-def get_all_parent_hexsha8s(commit):
+def get_all_parent_hexsha8s(commit: git.Commit):
    """Helper function to recursively get hexsha8 values for all parents of a commit."""
    unvisited = [commit]
    visited   = []
--- a/scripts/gen-unicode-data.py
+++ b/scripts/gen-unicode-data.py
@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import array
 import unicodedata
 import requests
@ -133,7 +135,7 @@ table_nfd.sort()


 # group ranges with same flags
-ranges_flags = [(0, codepoint_flags[0])]  # start, flags
+ranges_flags: list[tuple[int, int]] = [(0, codepoint_flags[0])]  # start, flags
 for codepoint, flags in enumerate(codepoint_flags):
    if flags != ranges_flags[-1][1]:
        ranges_flags.append((codepoint, flags))
@ -141,11 +143,11 @@ ranges_flags.append((MAX_CODEPOINTS, 0x0000))


 # group ranges with same nfd
-ranges_nfd = [(0, 0, 0)]  # start, last, nfd
+ranges_nfd: list[tuple[int, int, int]] = [(0, 0, 0)]  # start, last, nfd
 for codepoint, norm in table_nfd:
    start = ranges_nfd[-1][0]
    if ranges_nfd[-1] != (start, codepoint - 1, norm):
-        ranges_nfd.append(None)
+        ranges_nfd.append(None)  # type: ignore[arg-type]  # dummy, will be replaced below
        start = codepoint
    ranges_nfd[-1] = (start, codepoint, norm)

@ -179,13 +181,13 @@ for codepoint in table_whitespace:
 out("};\n")

 out("const std::unordered_map<uint32_t, uint32_t> unicode_map_lowercase = {")
-for tuple in table_lowercase:
-    out("{0x%06X, 0x%06X}," % tuple)
+for tuple_lw in table_lowercase:
+    out("{0x%06X, 0x%06X}," % tuple_lw)
 out("};\n")

 out("const std::unordered_map<uint32_t, uint32_t> unicode_map_uppercase = {")
-for tuple in table_uppercase:
-    out("{0x%06X, 0x%06X}," % tuple)
+for tuple_up in table_uppercase:
+    out("{0x%06X, 0x%06X}," % tuple_up)
 out("};\n")

 out("const std::vector<range_nfd> unicode_ranges_nfd = {  // start, last, nfd")
--- a/scripts/sync-ggml-am.sh
+++ b/scripts/sync-ggml-am.sh
@ -63,6 +63,7 @@ while read c; do
        src/ggml*.metal \
        src/ggml*.cu \
        src/ggml-cuda/* \
+        src/ggml-sycl/* \
        include/ggml*.h \
        tests/test-opt.cpp \
        tests/test-grad0.cpp \
@ -113,6 +114,7 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
    # src/ggml-quants.c       -> ggml/src/ggml-quants.c
    # src/ggml-quants.h       -> ggml/src/ggml-quants.h
    # src/ggml-rpc.cpp        -> ggml/src/ggml-rpc.cpp
+    # src/ggml-sycl/*         -> ggml/src/ggml-sycl/
    # src/ggml-sycl.cpp       -> ggml/src/ggml-sycl.cpp
    # src/ggml-vulkan.cpp     -> ggml/src/ggml-vulkan.cpp
    #
@ -153,6 +155,7 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
        -e 's/([[:space:]]|[ab]\/)src\/ggml-quants\.c/\1ggml\/src\/ggml-quants.c/g' \
        -e 's/([[:space:]]|[ab]\/)src\/ggml-quants\.h/\1ggml\/src\/ggml-quants.h/g' \
        -e 's/([[:space:]]|[ab]\/)src\/ggml-rpc\.cpp/\1ggml\/src\/ggml-rpc.cpp/g' \
+        -e 's/([[:space:]]|[ab]\/)src\/ggml-sycl\//\1ggml\/src\/ggml-sycl\//g' \
        -e 's/([[:space:]]|[ab]\/)src\/ggml-sycl\.cpp/\1ggml\/src\/ggml-sycl.cpp/g' \
        -e 's/([[:space:]]|[ab]\/)src\/ggml-vulkan\.cpp/\1ggml\/src\/ggml-vulkan.cpp/g' \
        -e 's/([[:space:]]|[ab]\/)include\/ggml\.h/\1ggml\/include\/ggml.h/g' \
--- a/scripts/sync-ggml.last
+++ b/scripts/sync-ggml.last
@ -1 +1 @@
-5378ea0d3c2f25bcd330ecb226ad2db454be86d0
+e3b3846976c94163f2b3dd128cc959782653edbb
--- a/scripts/sync-ggml.sh
+++ b/scripts/sync-ggml.sh
@ -18,6 +18,7 @@ cp -rpv ../ggml/src/ggml-metal.metal    ./ggml/src/ggml-metal.metal
 cp -rpv ../ggml/src/ggml-quants.c       ./ggml/src/ggml-quants.c
 cp -rpv ../ggml/src/ggml-quants.h       ./ggml/src/ggml-quants.h
 cp -rpv ../ggml/src/ggml-rpc.cpp        ./ggml/src/ggml-rpc.cpp
+cp -rpv ../ggml/src/ggml-sycl/*         ./ggml/src/ggml-sycl/
 cp -rpv ../ggml/src/ggml-sycl.cpp       ./ggml/src/ggml-sycl.cpp
 cp -rpv ../ggml/src/ggml-vulkan.cpp     ./ggml/src/ggml-vulkan.cpp

--- a/src/llama.cpp
+++ b/src/llama.cpp
@ -57,6 +57,12 @@
    #include <io.h>
 #endif

+#if __cplusplus >= 202000L
+    #define LU8(x) (const char*)(u8##x)
+#else
+    #define LU8(x) u8##x
+#endif
+
 #include <algorithm>
 #include <array>
 #include <cassert>
@ -3836,6 +3842,9 @@ struct llama_model_loader {
                case GGML_TYPE_IQ4_NL:  ftype = LLAMA_FTYPE_MOSTLY_IQ4_NL;  break;
                case GGML_TYPE_IQ4_XS:  ftype = LLAMA_FTYPE_MOSTLY_IQ4_XS;  break;
                case GGML_TYPE_IQ3_S:   ftype = LLAMA_FTYPE_MOSTLY_IQ3_S;   break;
+                case GGML_TYPE_Q4_0_4_4: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_4; break;
+                case GGML_TYPE_Q4_0_4_8: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_8; break;
+                case GGML_TYPE_Q4_0_8_8: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_8_8; break;
                default:
                    {
                        LLAMA_LOG_WARN("%s: unknown type %s\n", __func__, ggml_type_name(type_max));
@ -4529,6 +4538,9 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
        case LLAMA_FTYPE_MOSTLY_IQ4_XS: return "IQ4_XS - 4.25 bpw";
        case LLAMA_FTYPE_MOSTLY_IQ3_S:  return "IQ3_S - 3.4375 bpw";
        case LLAMA_FTYPE_MOSTLY_IQ3_M:  return "IQ3_S mix - 3.66 bpw";
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: return "Q4_0_4_4";
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: return "Q4_0_4_8";
+        case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: return "Q4_0_8_8";

        default: return "unknown, may not work";
    }
@ -13282,6 +13294,8 @@ struct llm_build_context {
                    LLM_NORM_RMS, cb, -1);
            cb(cur, "result_norm", -1);
        } else {
+            GGML_ASSERT(n_outputs_enc > 0 && "call llama_encode() first");
+
            struct ggml_tensor * embd_enc       = llm_build_inp_embd_enc();
            struct ggml_tensor * pos_bucket_dec = llm_build_pos_bucket(true);

@ -17842,6 +17856,10 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) {
                new_type = GGML_TYPE_IQ3_S;
            }
+            else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 ||
+                     new_type == GGML_TYPE_Q4_0_8_8) {
+                new_type = GGML_TYPE_Q4_0;
+            }
        }
    } else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS || ftype == LLAMA_FTYPE_MOSTLY_IQ1_S ||
               ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M    || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M) {
@ -18154,6 +18172,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
        case LLAMA_FTYPE_MOSTLY_IQ4_XS:  default_type = GGML_TYPE_IQ4_XS;  break;
        case LLAMA_FTYPE_MOSTLY_IQ3_S:   default_type = GGML_TYPE_IQ3_S;   break;
        case LLAMA_FTYPE_MOSTLY_IQ3_M:   default_type = GGML_TYPE_IQ3_S;   break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: default_type = GGML_TYPE_Q4_0_4_4; break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: default_type = GGML_TYPE_Q4_0_4_8; break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: default_type = GGML_TYPE_Q4_0_8_8; break;

        default: throw std::runtime_error(format("invalid output file type %d\n", ftype));
    }
@ -18464,6 +18485,14 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
                f32_data = (float *) f32_conv_buf.data();
            }

+            int chunk_size_multiplier = 1;
+            if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 || new_type == GGML_TYPE_Q4_0_8_8) {
+                if ((new_type == GGML_TYPE_Q4_0_8_8) && (tensor->ne[1] % 8 != 0)) new_type = GGML_TYPE_Q4_0;
+                else if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q4_0;
+                if (new_type == GGML_TYPE_Q4_0_8_8) chunk_size_multiplier = 8;
+                else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8) chunk_size_multiplier = 4;
+            }
+
            LLAMA_LOG_INFO("converting to %s .. ", ggml_type_name(new_type));
            fflush(stdout);

@ -18476,7 +18505,8 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
            const int64_t nrows = tensor->ne[1];

            static const int64_t min_chunk_size = 32 * 512;
-            const int64_t chunk_size = n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row);
+            const int64_t chunk_size = (n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row)) *
+                                       chunk_size_multiplier;

            const int64_t nelements_matrix = tensor->ne[0] * tensor->ne[1];
            const int64_t nchunk = (nelements_matrix + chunk_size - 1)/chunk_size;
@ -21508,12 +21538,12 @@ static int32_t llama_chat_apply_template_internal(
        if (add_ass) {
            ss << "<|assistant|>";
        }
-    } else if (tmpl == "minicpm" || tmpl_contains(u8"<用户>")) {
+    } else if (tmpl == "minicpm" || tmpl_contains(LU8("<用户>"))) {
        // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
        for (auto message : chat) {
            std::string role(message->role);
            if (role == "user") {
-                ss << u8"<用户>";
+                ss << LU8("<用户>");
                ss << trim(message->content);
                ss << "<AI>";
            } else {
@ -21529,7 +21559,7 @@ static int32_t llama_chat_apply_template_internal(
            } else if (role == "user") {
                ss << "User: " << message->content << "\n\n";
            } else if (role == "assistant") {
-                ss << "Assistant: " << message->content << u8"<｜end▁of▁sentence｜>";
+                ss << "Assistant: " << message->content << LU8("<｜end▁of▁sentence｜>");
            }
        }
        if (add_ass) {
--- a/src/unicode.cpp
+++ b/src/unicode.cpp
@ -1,3 +1,7 @@
+#if defined(_MSC_VER)
+#define _SILENCE_CXX17_CODECVT_HEADER_DEPRECATION_WARNING
+#endif
+
 #include "unicode.h"
 #include "unicode-data.h"

--- a/tests/test-backend-ops.cpp
+++ b/tests/test-backend-ops.cpp
@ -1266,6 +1266,32 @@ struct test_pool2d : public test_case {
    }
 };

+// GGML_OP_CONV_TRANSPOSE_1D
+struct test_conv_transpose_1d : public test_case {
+    const std::array<int64_t, 4> ne_input;
+    const std::array<int64_t, 4> ne_kernel;
+
+    const int s0; // stride
+    const int p0; // padding
+    const int d0; // dilation
+
+    std::string vars() override {
+        return VARS_TO_STR5(ne_input, ne_kernel, s0, p0, d0);
+    }
+
+    test_conv_transpose_1d(std::array<int64_t, 4> ne_input = {197, 32, 1, 1}, // [input_width, input_height, input_channels, 1]
+                           std::array<int64_t, 4> ne_kernel = {16, 32, 32, 1}, // [kernel_width, kernel_height, input_channels, 1]
+                           int s0 = 1, int p0 = 0, int d0 = 1)
+        : ne_input(ne_input), ne_kernel(ne_kernel), s0(s0), p0(p0), d0(d0) {}
+
+    ggml_tensor * build_graph(ggml_context * ctx) override {
+        ggml_tensor * input = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne_input.data());
+        ggml_tensor * kernel = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne_kernel.data());
+        ggml_tensor * out = ggml_conv_transpose_1d(ctx, kernel, input, s0, p0, d0);
+        return out;
+    }
+};
+
 // GGML_OP_IM2COL
 struct test_im2col : public test_case {
    const ggml_type type_input;
@ -1279,7 +1305,7 @@ struct test_im2col : public test_case {
    // padding
    const int p0;
    const int p1;
-    // dilatation
+    // dilation
    const int d0;
    const int d1;
    // mode
@ -2098,6 +2124,16 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
    test_cases.emplace_back(new test_im2col(GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_F32));
    test_cases.emplace_back(new test_im2col(GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_F16));

+    test_cases.emplace_back(new test_conv_transpose_1d());
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {2,3,2,1}, 3, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {2,3,2,1}, 2, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {2,3,2,1}, 1, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {3,2,2,1}, 2, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {3,2,2,1}, 1, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {3,1,2,1}, 1, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({2,1,1,1}, {3,1,1,1}, 1, 0, 1));
+
+
    test_cases.emplace_back(new test_repeat(GGML_TYPE_F32, {10, 10, 10, 10}, {1, 1, 1, 1}));
    test_cases.emplace_back(new test_repeat(GGML_TYPE_F32, {10, 10, 10, 10}, {2, 1, 1, 1}));
    test_cases.emplace_back(new test_repeat(GGML_TYPE_F32, {10, 10, 10, 10}, {1, 2, 1, 1}));
--- a/tests/test-tokenizer-random.py
+++ b/tests/test-tokenizer-random.py
@ -6,6 +6,8 @@
 #   python3 tests/test-tokenizer-random.py ./models/ggml-vocab-llama-bpe.gguf ./models/tokenizers/llama-bpe
 #

+from __future__ import annotations
+
 import time
 import logging
 import argparse
@ -13,7 +15,9 @@ import subprocess
 import random
 import unicodedata

-from typing import Iterator
+from pathlib import Path
+from typing import Any, Iterator, cast
+from typing_extensions import Buffer

 import cffi
 from transformers import AutoTokenizer
@ -28,15 +32,15 @@ class LibLlama:
    DEFAULT_PATH_INCLUDES = ["./ggml/include/", "./include/"]
    DEFAULT_PATH_LIBLLAMA = "./build/src/libllama.so"  # CMakeLists.txt: BUILD_SHARED_LIBS ON

-    def __init__(self, path_llama_h: str = None, path_includes: list[str] = [], path_libllama: str = None):
+    def __init__(self, path_llama_h: str | None = None, path_includes: list[str] = [], path_libllama: str | None = None):
        path_llama_h = path_llama_h or self.DEFAULT_PATH_LLAMA_H
        path_includes = path_includes or self.DEFAULT_PATH_INCLUDES
        path_libllama = path_libllama or self.DEFAULT_PATH_LIBLLAMA
        (self.ffi, self.lib) = self._load_libllama_cffi(path_llama_h, path_includes, path_libllama)
        self.lib.llama_backend_init()

-    def _load_libllama_cffi(self, path_llama_h: str, path_includes: list[str], path_libllama: str):
-        cmd = ["gcc", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)="]
+    def _load_libllama_cffi(self, path_llama_h: str, path_includes: list[str], path_libllama: str) -> tuple[cffi.FFI, Any]:
+        cmd = ["gcc", "-O0", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)="]
        cmd += ["-I" + path for path in path_includes] + [path_llama_h]
        res = subprocess.run(cmd, stdout=subprocess.PIPE)
        assert (res.returncode == 0)
@ -68,7 +72,7 @@ class LibLlama:
 class LibLlamaModel:

    def __init__(self, libllama: LibLlama, path_model: str, mparams={}, cparams={}):
-        self.lib = libllama.lib
+        self.lib: Any = libllama.lib
        self.ffi = libllama.ffi
        if isinstance(mparams, dict):
            mparams = libllama.model_default_params(**mparams)
@ -94,11 +98,11 @@ class LibLlamaModel:
        self.lib = None

    def tokenize(self, text: str, add_special: bool = False, parse_special: bool = False) -> list[int]:
-        text = text.encode("utf-8")
-        num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, len(self.token_ids), add_special, parse_special)
+        encoded_text: bytes = text.encode("utf-8")
+        num = self.lib.llama_tokenize(self.model, encoded_text, len(encoded_text), self.token_ids, len(self.token_ids), add_special, parse_special)
        while num < 0 and len(self.token_ids) < (16 << 20):
            self.token_ids = self.ffi.new("llama_token[]", -2 * num)
-            num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, len(self.token_ids), add_special, parse_special)
+            num = self.lib.llama_tokenize(self.model, encoded_text, len(encoded_text), self.token_ids, len(self.token_ids), add_special, parse_special)
        return list(self.token_ids[0:num])

    def detokenize(self, ids: list[int], remove_special: bool = False, unparse_special: bool = False) -> str:
@ -110,7 +114,7 @@ class LibLlamaModel:
        while num < 0 and len(self.text_buff) < (16 << 20):
            self.text_buff = self.ffi.new("uint8_t[]", -2 * num)
            num = self.lib.llama_detokenize(self.model, self.token_ids, len(ids), self.text_buff, len(self.text_buff), remove_special, unparse_special)
-        return str(self.ffi.buffer(self.text_buff, num), encoding="utf-8", errors="replace")  # replace errors with '\uFFFD'
+        return str(cast(Buffer, self.ffi.buffer(self.text_buff, num)), encoding="utf-8", errors="replace")  # replace errors with '\uFFFD'


 class Tokenizer:
@ -152,7 +156,7 @@ class TokenizerGroundtruth (Tokenizer):

 class TokenizerLlamaCpp (Tokenizer):

-    libllama: LibLlama = None
+    libllama: LibLlama | None = None

    def __init__(self, vocab_file: str):
        if not self.libllama:
@ -404,7 +408,7 @@ def generator_random_vocab_words(tokenizer: TokenizerGroundtruth, iterations=100

 def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLlamaCpp, generator: Iterator[str]):

-    def find_first_mismatch(ids1: list[int], ids2: list[int]):
+    def find_first_mismatch(ids1: list[int] | str, ids2: list[int] | str):
        for i, (a, b) in enumerate(zip(ids1, ids2)):
            if a != b:
                return i
@ -433,7 +437,7 @@ def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLl
    decode_errors = 0
    MAX_ERRORS = 10

-    logger.info("%s: %s" % (generator.__name__, "ini"))
+    logger.info("%s: %s" % (generator.__qualname__, "ini"))
    for text in generator:
        # print(repr(text), text.encode())
        # print(repr(text), hex(ord(text[0])), text.encode())
@ -472,13 +476,13 @@ def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLl
            break

    t_total = time.perf_counter() - t_start
-    logger.info(f"{generator.__name__}: end,  {t_encode1=:.3f} {t_encode2=:.3f}  {t_decode1=:.3f} {t_decode2=:.3f}  {t_total=:.3f}")
+    logger.info(f"{generator.__qualname__}: end,  {t_encode1=:.3f} {t_encode2=:.3f}  {t_decode1=:.3f} {t_decode2=:.3f}  {t_total=:.3f}")


-def main(argv: list[str] = None):
+def main(argv: list[str] | None = None):
    parser = argparse.ArgumentParser()
-    parser.add_argument("vocab_file", help="path to vocab 'gguf' file")
-    parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")
+    parser.add_argument("vocab_file", type=str, help="path to vocab 'gguf' file")
+    parser.add_argument("dir_tokenizer", type=str, help="directory containing 'tokenizer.model' file")
    parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
    args = parser.parse_args(argv)

@ -520,7 +524,7 @@ if __name__ == "__main__":
        format   = "%(levelname)s %(message)s",
    )

-    path_tokenizers   = "./models/tokenizers/"
+    path_tokenizers   = Path("./models/tokenizers/")
    path_vocab_format = "./models/ggml-vocab-%s.gguf"

    tokenizers = [
@ -556,6 +560,6 @@ if __name__ == "__main__":
    for tokenizer in tokenizers:
        logger.info("-" * 50)
        logger.info(f"TOKENIZER: '{tokenizer}'")
-        vocab_file = path_vocab_format % tokenizer
-        dir_tokenizer = path_tokenizers + "/" + tokenizer
-        main([vocab_file, dir_tokenizer, "--verbose"])
+        vocab_file = Path(path_vocab_format % tokenizer)
+        dir_tokenizer = path_tokenizers / tokenizer
+        main([str(vocab_file), str(dir_tokenizer), "--verbose"])