* lora: load to devide buft
* add patch tensor function
* correct tensor patch
* llama_lora_adapter_apply
* correct ggml_backend_tensor_copy
* add llm_build_mm
* fix auto merge
* update based on review comments
* add convert script
* no more transpose A
* add f16 convert
* add metadata check
* add sanity check
* fix ftype
* add requirements
* fix requirements
* fix outfile
* conversion: only allow selected models
* fix types
* cuda : do not use dmmv if the tensor does not have enough cols
* llama : lora fixes
* do not disable mmap with lora
Co-authored-by: slaren <slarengh@gmail.com>
* llm_build_lora_mm_id
* convert_lora : MoE LoRA conversion support
* convert_lora : prefer safetensors, similarly to convert_hf
* convert_hf : simplify modify_tensors for InternLM2
* convert_lora : lazy conversion
* llama : load and use alpha from LoRA adapters
* llama : use llm_build_lora_mm in most model graphs
* auto scale
* Revert "auto scale"
This reverts commit 42415a4874.
* remove redundant params
* Apply suggestions from code review
Co-authored-by: slaren <slarengh@gmail.com>
* change kv metadata
* move add_type to __init__
* convert_hf : move add_type to main()
* convert_lora : use the GGUFWriter from Model instead of overwriting it
---------
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Francis Couture-Harpin <git@compilade.net>
* 9B - query_pre_attn_scalar = 256 not 224
See 03e657582d
Gemma 9b should use 256 and not 224 (self.config.hidden_size // self.config.num_attention_heads)
* llama : fix Gemma-2 Query scaling factor
ggml-ci
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* llama : fix mpt and olmo pre-tokenizer
* llama : pre-tokenize non-special user-defined tokens first
* llama : fix detection of control-like user-defined tokens
* convert_hf : identify which user-defined tokens are control tokens
Only used in _set_vocab_gpt2() for now.
* convert_hf : identify more added control tokens for SPM tokenziers
This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly,
including HTML tags and consecutive spaces,
but it unfortunately requires model re-conversion.
There seems to be a weird behavior of the HF tokenizer for Gemma,
which prefers to use the 16-space token over more lengthy space tokens,
while using the SentencePiece tokenizer does not do this.
(the implementation in llama.cpp has the same behavior as SentencePiece)
* llama : fix wrong pre-tokenization of byte tokens
* llama : fix Viking pre-tokenizer regex
The order was previously wrong, which caused errors in some tests.
* llama : fix command-r detokenization
* convert_hf : reduce usages of the UNKNOWN token type
* llama : add UNKNOWN tokens in the special tokens cache
* convert_hf : reduce usages of UNKNOWN for InternLM2
This makes the changes from #8321 more consistent
with the other changes made here.
* test-tokenizer-random : reduce potential confilcts with #8379
* test-tokenizer-random : add a failing edge case for falcon
The <filename> token used by Refact doesn't serve
the same purpose as the <file_separator> from CodeGemma.
Signed-off-by: Jiri Podivin <jpodivin@redhat.com>
* py : type-check all Python scripts with Pyright
* server-tests : use trailing slash in openai base_url
* server-tests : add more type annotations
* server-tests : strip "chat" from base_url in oai_chat_completions
* server-tests : model metadata is a dict
* ci : disable pip cache in type-check workflow
The cache is not shared between branches, and it's 250MB in size,
so it would become quite a big part of the 10GB cache limit of the repo.
* py : fix new type errors from master branch
* tests : fix test-tokenizer-random.py
Apparently, gcc applies optimisations even when pre-processing,
which confuses pycparser.
* ci : only show warnings and errors in python type-check
The "information" level otherwise has entries
from 'examples/pydantic_models_to_grammar.py',
which could be confusing for someone trying to figure out what failed,
considering that these messages can safely be ignored
even though they look like errors.
* add chatglm3-6b model support huggingface model:
https://hf-mirror.com/THUDM/chatglm3-6b
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* remove .rotary_pos_emb.inv_freq and unuse code for chatglm3 model
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* fix lint error
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* optimize convert-hf-to-gguf.py for chatglm model
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* support glm-4-9b-chat
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* fix eos tokens to glm4
* remove unused log
* add preprocess to chatglm3 and chatglm4
* add eos_id_list to llama.cpp
* fix code style
* fix code style
* fix conflicts
* fix conflicts
* Revert "add eos_id_list to llama.cpp"
This reverts commit 3a4d5790bf.
* set <|endoftext|> as eos and <|user|> as eot
* fix chat template bug
* add comment to glm prefix and suffix
* fix conflicts and add rope_ratio & ChatGLMForConditionalGeneration
* fix chat template bug
* fix codestyle
* fix conflicts
* modified the general name of glm model
* fix conflicts
* remove prefix and suffix
* use normal glm4 chattempalte & use LLM_FFN_SWIGLU in phi3
* fix: resolve Flake8 errors in `convert-hf-to-gguf.py`
- Fix E302 by adding two blank lines before top-level function definitions
- Replace print statements to fix NP100
- Fix E303 by ensuring only one blank line between lines of code
* fix rope ratio to solve incorrect answers
* fix by comments
---------
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
Co-authored-by: XingXing Qiao <qiaoxx@dingdao.com>
Co-authored-by: Umpire2018 <138990495+Umpire2018@users.noreply.github.com>
* Initial OpenELM support (270M only so far)
* Fill out missing entries in llama_model_type_name
* fixup! Initial OpenELM support (270M only so far)
Fix formatting
* llama : support all OpenELM models
* llama : add variable GQA and variable FFN sizes
Some metadata keys can now also be arrays to support setting
their value per-layer for models like OpenELM.
* llama : minor spacing changes
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : use std::array for per-layer hparams
* llama : fix save/load state
* llama : do not print hparams for vocab-only models
* llama : handle n_head == 0
* llama : use const ref for print_f and fix division by zero
* llama : fix t5 uses of n_head and n_ff
* llama : minor comment
---------
Co-authored-by: Francis Couture-Harpin <git@compilade.net>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
