From 866c0113fbd070a42839f09042fed5e951af1b33 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 25 Sep 2024 20:39:25 +0300 Subject: [PATCH] jina : support v1 reranker --- convert_hf_to_gguf.py | 10 ++++++++++ convert_hf_to_gguf_update.py | 1 + gguf-py/gguf/constants.py | 1 + gguf-py/gguf/tensor_mapping.py | 1 + src/llama.cpp | 34 ++++++++++++++++++++++++++-------- 5 files changed, 39 insertions(+), 8 deletions(-) diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index d69a0d9f8..c7885f85e 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -597,6 +597,9 @@ class Model: if chkhsh == "a8594e3edff7c29c003940395316294b2c623e09894deebbc65f33f1515df79e": # ref: https://huggingface.co/databricks/dbrx-base res = "dbrx" + if chkhsh == "c7699093ba4255a91e702aa38a596aa81669f3525dae06c2953267dde580f448": + # ref: https://huggingface.co/jinaai/jina-reranker-v1-tiny-en + res = "jina-v1-en" if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f": # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-en res = "jina-v2-en" @@ -3117,6 +3120,13 @@ class JinaBertV2Model(BertModel): self.gguf_writer.add_add_bos_token(True) self.gguf_writer.add_add_eos_token(True) + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + # if name starts with "bert.", remove the prefix + # e.g. https://huggingface.co/jinaai/jina-reranker-v1-tiny-en + if name.startswith("bert."): + name = name[5:] + + return super().modify_tensors(data_torch, name, bid) @Model.register("OpenELMForCausalLM") class OpenELMModel(Model): diff --git a/convert_hf_to_gguf_update.py b/convert_hf_to_gguf_update.py index 021f65abd..527bc44e5 100755 --- a/convert_hf_to_gguf_update.py +++ b/convert_hf_to_gguf_update.py @@ -81,6 +81,7 @@ models = [ {"name": "qwen2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen1.5-7B", }, {"name": "olmo", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/allenai/OLMo-1.7-7B-hf", }, {"name": "dbrx", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/databricks/dbrx-base", }, + {"name": "jina-v1-en", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-reranker-v1-tiny-en", }, {"name": "jina-v2-en", "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-en", }, # WPM! {"name": "jina-v2-es", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-es", }, {"name": "jina-v2-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", }, diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 414a3ae21..f7e1290e6 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -647,6 +647,7 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = { MODEL_TENSOR.FFN_GATE, MODEL_TENSOR.FFN_DOWN, MODEL_TENSOR.LAYER_OUT_NORM, + MODEL_TENSOR.CLS, ], MODEL_ARCH.MPT: [ MODEL_TENSOR.TOKEN_EMBD, diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index 4a34a549d..48d359071 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -681,6 +681,7 @@ class TensorNameMap: ), MODEL_TENSOR.CLS: ( + "classifier", # jina "classifier.dense", # roberta ), diff --git a/src/llama.cpp b/src/llama.cpp index b7c0fa4f4..39f592cd1 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -828,6 +828,7 @@ static const std::map> LLM_TENSOR_NA { LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" }, { LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" }, { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" }, + { LLM_TENSOR_CLS, "cls" }, }, }, { @@ -5590,11 +5591,11 @@ static void llm_load_hparams( ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps); ml.get_key(LLM_KV_ATTENTION_CAUSAL, hparams.causal_attn); ml.get_key(LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT, hparams.n_vocab_type); - ml.get_key(LLM_KV_POOLING_TYPE, hparams.pooling_type); + ml.get_key(LLM_KV_POOLING_TYPE, hparams.pooling_type, false); hparams.f_max_alibi_bias = 8.0f; switch (hparams.n_layer) { - case 4: model.type = e_model::MODEL_33M; break; // jina-embeddings-small + case 4: model.type = e_model::MODEL_33M; break; // jina-embeddings-small case 12: model.type = e_model::MODEL_137M; break; // jina-embeddings-base } } break; @@ -6287,6 +6288,7 @@ static void llm_load_vocab( tokenizer_pre == "phi-2" || tokenizer_pre == "jina-es" || tokenizer_pre == "jina-de" || + tokenizer_pre == "jina-v1-en" || tokenizer_pre == "jina-v2-es" || tokenizer_pre == "jina-v2-de" || tokenizer_pre == "jina-v2-code") { @@ -6408,7 +6410,12 @@ static void llm_load_vocab( for (uint32_t i = 0; i < n_vocab; i++) { std::string word = gguf_get_arr_str(ctx, token_idx, i); - GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0); + + //GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0); + if (word.empty()) { + LLAMA_LOG_WARN("%s: empty token at index %u\n", __func__, i); + word = "[EMPTY_" + std::to_string(i) + "]"; + } vocab.token_to_id[word] = i; vocab.max_token_len = std::max(vocab.max_token_len, (int) word.size()); @@ -6487,8 +6494,14 @@ static void llm_load_vocab( vocab.linefeed_id = ids[0]; } else { const std::vector ids = llama_tokenize_internal(vocab, "\xC4\x8A", false); // U+010A - GGML_ASSERT(!ids.empty() && "model vocab missing newline token"); - vocab.linefeed_id = ids[0]; + + //GGML_ASSERT(!ids.empty() && "model vocab missing newline token"); + if (ids.empty()) { + LLAMA_LOG_WARN("%s: model vocab missing newline token, using special_pad_id instead\n", __func__); + vocab.linefeed_id = vocab.special_pad_id; + } else { + vocab.linefeed_id = ids[0]; + } } // special tokens @@ -7419,6 +7432,8 @@ static bool llm_load_tensors( model.tok_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "weight"), {n_embd}); // LayerNorm model.tok_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "bias"), {n_embd}); //LayerNorm bias + model.cls = ml.create_tensor(ctx_output, tn(LLM_TENSOR_CLS, "weight"), {n_embd, 1}, llama_model_loader::TENSOR_NOT_REQUIRED); + model.cls_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_CLS, "bias"), {1}, llama_model_loader::TENSOR_NOT_REQUIRED); for (int i = 0; i < n_layer; ++i) { ggml_context * ctx_layer = ctx_for_layer(i); ggml_context * ctx_split = ctx_for_layer_split(i); @@ -10237,12 +10252,15 @@ struct llm_build_context { // https://github.com/huggingface/transformers/blob/5af7d41e49bbfc8319f462eb45253dcb3863dfb7/src/transformers/models/roberta/modeling_roberta.py#L1566 GGML_ASSERT(model.cls != nullptr); GGML_ASSERT(model.cls_b != nullptr); - GGML_ASSERT(model.cls_out != nullptr); - GGML_ASSERT(model.cls_out_b != nullptr); cur = ggml_add (ctx0, ggml_mul_mat(ctx0, model.cls, inp), model.cls_b); cur = ggml_tanh(ctx0, cur); - cur = ggml_add (ctx0, ggml_mul_mat(ctx0, model.cls_out, cur), model.cls_out_b); + + if (model.cls_out) { + GGML_ASSERT(model.cls_out_b != nullptr); + + cur = ggml_add (ctx0, ggml_mul_mat(ctx0, model.cls_out, cur), model.cls_out_b); + } } break; default: {