diff --git a/README.md b/README.md index c6b72443..78312e07 100644 --- a/README.md +++ b/README.md @@ -107,7 +107,7 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/ [24/02/05] Qwen1.5 (Qwen2 beta version) series models are supported in LLaMA-Factory. Check this [blog post](https://qwenlm.github.io/blog/qwen1.5/) for details. -[24/01/18] We supported **agent tuning** for most models, equipping model with tool using abilities by fine-tuning with `dataset: glaive_toolcall`. +[24/01/18] We supported **agent tuning** for most models, equipping model with tool using abilities by fine-tuning with `dataset: glaive_toolcall_en`. [23/12/23] We supported **[unsloth](https://github.com/unslothai/unsloth)**'s implementation to boost LoRA tuning for the LLaMA, Mistral and Yi models. Try `use_unsloth: true` argument to activate unsloth patch. It achieves **170%** speed in our benchmark, check [this page](https://github.com/hiyouga/LLaMA-Factory/wiki/Performance-comparison) for details. @@ -164,7 +164,7 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/ | [OLMo](https://huggingface.co/allenai) | 1B/7B | q_proj,v_proj | - | | [PaliGemma](https://huggingface.co/google) | 3B | q_proj,v_proj | gemma | | [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | q_proj,v_proj | - | -| [Phi-3](https://huggingface.co/microsoft) | 3.8B | qkv_proj | phi | +| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | qkv_proj | phi | | [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | c_attn | qwen | | [Qwen1.5 (Code/MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B/110B | q_proj,v_proj | qwen | | [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | q_proj,v_proj | - | @@ -403,20 +403,6 @@ See [examples/README.md](examples/README.md) for advanced usage (including distr CUDA_VISIBLE_DEVICES=0 GRADIO_SHARE=1 llamafactory-cli webui ``` -
For Alibaba Cloud PAI or AutoDL users - -If you encountered display problems in LLaMA Board on Alibaba Cloud PAI, try using the following command to set environment variables before starting LLaMA Board: - -```bash -export GRADIO_SERVER_PORT=7860 GRADIO_ROOT_PATH=/${JUPYTER_NAME}/proxy/7860/ -``` - -If you are using AutoDL, please install a specific version of Gradio: - -```bash -pip install gradio==4.10.0 -``` -
#### Use Docker diff --git a/README_zh.md b/README_zh.md index 5669e1ae..5acf3dd1 100644 --- a/README_zh.md +++ b/README_zh.md @@ -107,7 +107,7 @@ https://github.com/hiyouga/LLaMA-Factory/assets/16256802/ec36a9dd-37f4-4f72-81bd [24/02/05] Qwen1.5（Qwen2 测试版）系列模型已在 LLaMA-Factory 中实现微调支持。详情请查阅该[博客页面](https://qwenlm.github.io/zh/blog/qwen1.5/)。 -[24/01/18] 我们针对绝大多数模型实现了 **Agent 微调**，微调时指定 `dataset: glaive_toolcall` 即可使模型获得工具调用能力。 +[24/01/18] 我们针对绝大多数模型实现了 **Agent 微调**，微调时指定 `dataset: glaive_toolcall_zh` 即可使模型获得工具调用能力。 [23/12/23] 我们针对 LLaMA, Mistral 和 Yi 模型支持了 **[unsloth](https://github.com/unslothai/unsloth)** 的 LoRA 训练加速。请使用 `use_unsloth: true` 参数启用 unsloth 优化。该方法可提供 **170%** 的训练速度，详情请查阅[此页面](https://github.com/hiyouga/LLaMA-Factory/wiki/Performance-comparison)。 @@ -164,7 +164,7 @@ https://github.com/hiyouga/LLaMA-Factory/assets/16256802/ec36a9dd-37f4-4f72-81bd | [OLMo](https://huggingface.co/allenai) | 1B/7B | q_proj,v_proj | - | | [PaliGemma](https://huggingface.co/google) | 3B | q_proj,v_proj | gemma | | [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | q_proj,v_proj | - | -| [Phi-3](https://huggingface.co/microsoft) | 3.8B | qkv_proj | phi | +| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | qkv_proj | phi | | [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | c_attn | qwen | | [Qwen1.5 (Code/MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B/110B | q_proj,v_proj | qwen | | [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | q_proj,v_proj | - | @@ -403,22 +403,6 @@ CUDA_VISIBLE_DEVICES=0 llamafactory-cli export examples/merge_lora/llama3_lora_s CUDA_VISIBLE_DEVICES=0 GRADIO_SHARE=1 llamafactory-cli webui ``` -
阿里云 PAI 和 AutoDL 用户指南 - -如果您在阿里云 PAI 上使用 LLaMA Board 时遇到显示问题，请尝试在启动前使用以下命令设置环境变量： - -```bash -export GRADIO_SERVER_PORT=7860 GRADIO_ROOT_PATH=/${JUPYTER_NAME}/proxy/7860/ -``` - -如果您正在使用 AutoDL，请安装下述 Gradio 版本： - -```bash -pip install gradio==4.10.0 -``` - -
- #### 使用 Docker ```bash diff --git a/data/dataset_info.json b/data/dataset_info.json index 1deb3d6d..0a148431 100644 --- a/data/dataset_info.json +++ b/data/dataset_info.json @@ -262,6 +262,36 @@ "ruozhiba_gpt4": { "hf_hub_url": "hfl/ruozhiba_gpt4_turbo" }, + "llava_1k_en": { + "hf_hub_url": "BUAADreamer/llava-en-zh-2k", + "subset": "en", + "formatting": "sharegpt", + "columns": { + "messages": "messages", + "images": "images" + }, + "tags": { + "role_tag": "role", + "content_tag": "content", + "user_tag": "user", + "assistant_tag": "assistant" + } + }, + "llava_1k_zh": { + "hf_hub_url": "BUAADreamer/llava-en-zh-2k", + "subset": "zh", + "formatting": "sharegpt", + "columns": { + "messages": "messages", + "images": "images" + }, + "tags": { + "role_tag": "role", + "content_tag": "content", + "user_tag": "user", + "assistant_tag": "assistant" + } + }, "llava_150k_en": { "hf_hub_url": "BUAADreamer/llava-en-zh-300k", "subset": "en", diff --git a/examples/lora_single_gpu/llama3_lora_dpo.yaml b/examples/lora_single_gpu/llama3_lora_dpo.yaml index 958be1b5..f68244b7 100644 --- a/examples/lora_single_gpu/llama3_lora_dpo.yaml +++ b/examples/lora_single_gpu/llama3_lora_dpo.yaml @@ -6,6 +6,7 @@ stage: dpo do_train: true finetuning_type: lora lora_target: q_proj,v_proj +pref_beta: 0.1 pref_loss: sigmoid # [sigmoid (dpo), orpo, simpo] ### dataset diff --git a/src/llamafactory/chat/hf_engine.py b/src/llamafactory/chat/hf_engine.py index 5f0d02a7..2148f8cd 100644 --- a/src/llamafactory/chat/hf_engine.py +++ b/src/llamafactory/chat/hf_engine.py @@ -8,7 +8,6 @@ import torch from transformers import GenerationConfig, TextIteratorStreamer from ..data import get_template_and_fix_tokenizer -from ..extras.constants import IMAGE_TOKEN from ..extras.misc import get_logits_processor from ..model import load_model, load_tokenizer from .base_engine import BaseEngine, Response @@ -60,9 +59,9 @@ class HuggingfaceEngine(BaseEngine): processor is not None and image is not None and not hasattr(processor, "image_seq_length") - and IMAGE_TOKEN not in messages[0]["content"] + and template.image_token not in messages[0]["content"] ): # llava-like models - messages[0]["content"] = IMAGE_TOKEN + messages[0]["content"] + messages[0]["content"] = template.image_token + messages[0]["content"] paired_messages = messages + [{"role": "assistant", "content": ""}] system = system or generating_args["default_system"] @@ -75,7 +74,7 @@ class HuggingfaceEngine(BaseEngine): batch_feature = image_processor(image, return_tensors="pt") pixel_values = batch_feature.to(model.device)["pixel_values"] # shape (B, C, H, W) if hasattr(processor, "image_seq_length"): # paligemma models - image_token_id = tokenizer.convert_tokens_to_ids(IMAGE_TOKEN) + image_token_id = tokenizer.convert_tokens_to_ids(template.image_token) prompt_ids = [image_token_id] * getattr(processor, "image_seq_length") + prompt_ids prompt_length = len(prompt_ids) diff --git a/src/llamafactory/chat/vllm_engine.py b/src/llamafactory/chat/vllm_engine.py index e424481f..3310a864 100644 --- a/src/llamafactory/chat/vllm_engine.py +++ b/src/llamafactory/chat/vllm_engine.py @@ -2,7 +2,6 @@ import uuid from typing import TYPE_CHECKING, AsyncGenerator, AsyncIterator, Dict, List, Optional, Sequence, Union from ..data import get_template_and_fix_tokenizer -from ..extras.constants import IMAGE_TOKEN from ..extras.logging import get_logger from ..extras.misc import get_device_count, infer_optim_dtype from ..extras.packages import is_vllm_available @@ -67,7 +66,7 @@ class VllmEngine(BaseEngine): patch_size = config.vision_config.patch_size self.image_feature_size = (image_size // patch_size) ** 2 engine_args["image_input_type"] = "pixel_values" - engine_args["image_token_id"] = self.tokenizer.convert_tokens_to_ids(IMAGE_TOKEN) + engine_args["image_token_id"] = self.tokenizer.convert_tokens_to_ids(self.template.image_token) engine_args["image_input_shape"] = "1,3,{},{}".format(image_size, image_size) engine_args["image_feature_size"] = self.image_feature_size if getattr(config, "is_yi_vl_derived_model", None): @@ -97,9 +96,9 @@ class VllmEngine(BaseEngine): self.processor is not None and image is not None and not hasattr(self.processor, "image_seq_length") - and IMAGE_TOKEN not in messages[0]["content"] - ): # llava-like models - messages[0]["content"] = IMAGE_TOKEN * self.image_feature_size + messages[0]["content"] + and self.template.image_token not in messages[0]["content"] + ): # llava-like models (TODO: paligemma models) + messages[0]["content"] = self.template.image_token * self.image_feature_size + messages[0]["content"] paired_messages = messages + [{"role": "assistant", "content": ""}] system = system or self.generating_args["default_system"] diff --git a/src/llamafactory/data/processors/feedback.py b/src/llamafactory/data/processors/feedback.py index 51db3e26..1aaff0ab 100644 --- a/src/llamafactory/data/processors/feedback.py +++ b/src/llamafactory/data/processors/feedback.py @@ -1,6 +1,6 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional -from ...extras.constants import IGNORE_INDEX, IMAGE_TOKEN +from ...extras.constants import IGNORE_INDEX from ...extras.logging import get_logger from .mm_utils import get_paligemma_token_type_ids, get_pixel_values @@ -46,7 +46,7 @@ def preprocess_feedback_dataset( continue if processor is not None and not hasattr(processor, "image_seq_length"): # llava-like models - examples["prompt"][i][0]["content"] = IMAGE_TOKEN + examples["prompt"][i][0]["content"] + examples["prompt"][i][0]["content"] = template.image_token + examples["prompt"][i][0]["content"] if examples["response"][i][0]["content"]: # desired example kto_tag = True @@ -82,7 +82,7 @@ def preprocess_feedback_dataset( kl_response_ids += [tokenizer.eos_token_id] if processor is not None and hasattr(processor, "image_seq_length"): # paligemma models - image_token_id = tokenizer.convert_tokens_to_ids(IMAGE_TOKEN) + image_token_id = tokenizer.convert_tokens_to_ids(template.image_token) prompt_ids = [image_token_id] * getattr(processor, "image_seq_length") + prompt_ids input_ids = prompt_ids + response_ids diff --git a/src/llamafactory/data/processors/pairwise.py b/src/llamafactory/data/processors/pairwise.py index ec0fb96e..69dab34a 100644 --- a/src/llamafactory/data/processors/pairwise.py +++ b/src/llamafactory/data/processors/pairwise.py @@ -1,6 +1,6 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional -from ...extras.constants import IGNORE_INDEX, IMAGE_TOKEN +from ...extras.constants import IGNORE_INDEX from ...extras.logging import get_logger from .mm_utils import get_paligemma_token_type_ids, get_pixel_values @@ -44,7 +44,7 @@ def preprocess_pairwise_dataset( continue if processor is not None and not hasattr(processor, "image_seq_length"): # llava-like models - examples["prompt"][i][0]["content"] = IMAGE_TOKEN + examples["prompt"][i][0]["content"] + examples["prompt"][i][0]["content"] = template.image_token + examples["prompt"][i][0]["content"] chosen_messages = examples["prompt"][i] + [examples["response"][i][0]] rejected_messages = examples["prompt"][i] + [examples["response"][i][1]] @@ -70,7 +70,7 @@ def preprocess_pairwise_dataset( rejected_ids += [tokenizer.eos_token_id] if processor is not None and hasattr(processor, "image_seq_length"): # paligemma models - image_token_id = tokenizer.convert_tokens_to_ids(IMAGE_TOKEN) + image_token_id = tokenizer.convert_tokens_to_ids(template.image_token) prompt_ids = [image_token_id] * getattr(processor, "image_seq_length") + prompt_ids chosen_input_ids = prompt_ids + chosen_ids diff --git a/src/llamafactory/data/processors/supervised.py b/src/llamafactory/data/processors/supervised.py index 80326d98..b119aa22 100644 --- a/src/llamafactory/data/processors/supervised.py +++ b/src/llamafactory/data/processors/supervised.py @@ -1,6 +1,6 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional -from ...extras.constants import IGNORE_INDEX, IMAGE_TOKEN +from ...extras.constants import IGNORE_INDEX from ...extras.logging import get_logger from .mm_utils import get_paligemma_token_type_ids, get_pixel_values @@ -37,13 +37,13 @@ def preprocess_supervised_dataset( continue if processor is not None and not hasattr(processor, "image_seq_length"): # llava-like models - examples["prompt"][i][0]["content"] = IMAGE_TOKEN + examples["prompt"][i][0]["content"] + examples["prompt"][i][0]["content"] = template.image_token + examples["prompt"][i][0]["content"] messages = examples["prompt"][i] + examples["response"][i] input_ids, labels = [], [] if processor is not None and hasattr(processor, "image_seq_length"): # paligemma models - image_token_id = tokenizer.convert_tokens_to_ids(IMAGE_TOKEN) + image_token_id = tokenizer.convert_tokens_to_ids(template.image_token) input_ids += [image_token_id] * getattr(processor, "image_seq_length") labels += [IGNORE_INDEX] * getattr(processor, "image_seq_length") diff --git a/src/llamafactory/data/processors/unsupervised.py b/src/llamafactory/data/processors/unsupervised.py index 4adf4f61..6a9f9460 100644 --- a/src/llamafactory/data/processors/unsupervised.py +++ b/src/llamafactory/data/processors/unsupervised.py @@ -1,6 +1,5 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional -from ...extras.constants import IMAGE_TOKEN from ...extras.logging import get_logger from ..utils import Role from .mm_utils import get_paligemma_token_type_ids, get_pixel_values @@ -37,7 +36,7 @@ def preprocess_unsupervised_dataset( continue if processor is not None and not hasattr(processor, "image_seq_length"): # llava-like models - examples["prompt"][i][0]["content"] = IMAGE_TOKEN + examples["prompt"][i][0]["content"] + examples["prompt"][i][0]["content"] = template.image_token + examples["prompt"][i][0]["content"] if len(examples["response"][i]) == 1: messages = examples["prompt"][i] + examples["response"][i] @@ -57,7 +56,7 @@ def preprocess_unsupervised_dataset( labels += [tokenizer.eos_token_id] if processor is not None and hasattr(processor, "image_seq_length"): # paligemma models - image_token_id = tokenizer.convert_tokens_to_ids(IMAGE_TOKEN) + image_token_id = tokenizer.convert_tokens_to_ids(template.image_token) input_ids = [image_token_id] * getattr(processor, "image_seq_length") + input_ids model_inputs["input_ids"].append(input_ids) diff --git a/src/llamafactory/data/template.py b/src/llamafactory/data/template.py index bf7133a9..979390ce 100644 --- a/src/llamafactory/data/template.py +++ b/src/llamafactory/data/template.py @@ -26,6 +26,7 @@ class Template: format_separator: "Formatter" default_system: str stop_words: List[str] + image_token: str efficient_eos: bool replace_eos: bool force_system: bool @@ -209,6 +210,7 @@ def _register_template( format_separator: Optional["Formatter"] = None, default_system: str = "", stop_words: List[str] = [], + image_token: str = "", efficient_eos: bool = False, replace_eos: bool = False, force_system: bool = False, @@ -256,6 +258,7 @@ def _register_template( format_separator=format_separator or default_separator_formatter, default_system=default_system, stop_words=stop_words, + image_token=image_token, efficient_eos=efficient_eos, replace_eos=replace_eos, force_system=force_system, @@ -730,7 +733,7 @@ _register_template( _register_template( name="mistral", - format_user=StringFormatter(slots=[" [INST] {{content}} [/INST]"]), + format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]), format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]), force_system=True, ) @@ -738,7 +741,7 @@ _register_template( _register_template( name="olmo", - format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>"]), + format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>\n"]), format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}]), format_system=StringFormatter(slots=[{"eos_token"}, "{{content}}"]), force_system=True, @@ -766,7 +769,6 @@ _register_template( name="phi", format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>\n"]), format_system=StringFormatter(slots=[{"bos_token"}, "<|system|>\n{{content}}<|end|>\n"]), - format_observation=StringFormatter(slots=["<|function_output|>\n{{content}}<|end|>\n<|assistant|>\n"]), format_separator=EmptyFormatter(slots=["\n"]), default_system="You are a helpful AI assistant.", stop_words=["<|end|>"], diff --git a/src/llamafactory/extras/constants.py b/src/llamafactory/extras/constants.py index 09c54899..087612fc 100644 --- a/src/llamafactory/extras/constants.py +++ b/src/llamafactory/extras/constants.py @@ -22,8 +22,6 @@ FILEEXT2TYPE = { IGNORE_INDEX = -100 -IMAGE_TOKEN = "" - LAYERNORM_NAMES = {"norm", "ln"} METHODS = ["full", "freeze", "lora"] @@ -327,6 +325,7 @@ register_model_group( }, "DeepSeek-MoE-16B-v2-Base": { DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite", + DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Lite", }, "DeepSeek-MoE-236B-Base": { DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2", @@ -338,6 +337,7 @@ register_model_group( }, "DeepSeek-MoE-16B-v2-Chat": { DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite-Chat", + DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Lite-Chat", }, "DeepSeek-MoE-236B-Chat": { DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Chat", @@ -430,6 +430,12 @@ register_model_group( DownloadSource.DEFAULT: "google/gemma-7b-it", DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b-it", }, + "Gemma-1.1-2B-Chat": { + DownloadSource.DEFAULT: "google/gemma-1.1-2b-it", + }, + "Gemma-1.1-7B-Chat": { + DownloadSource.DEFAULT: "google/gemma-1.1-7b-it", + }, }, template="gemma", ) @@ -437,16 +443,19 @@ register_model_group( register_model_group( models={ - "CodeGemma-2B": { - DownloadSource.DEFAULT: "google/codegemma-1.1-2b", - }, "CodeGemma-7B": { DownloadSource.DEFAULT: "google/codegemma-7b", }, "CodeGemma-7B-Chat": { - DownloadSource.DEFAULT: "google/codegemma-1.1-7b-it", + DownloadSource.DEFAULT: "google/codegemma-7b-it", DownloadSource.MODELSCOPE: "AI-ModelScope/codegemma-7b-it", }, + "CodeGemma-1.1-2B": { + DownloadSource.DEFAULT: "google/codegemma-1.1-2b", + }, + "CodeGemma-1.1-7B-Chat": { + DownloadSource.DEFAULT: "google/codegemma-1.1-7b-it", + }, }, template="gemma", ) @@ -635,6 +644,12 @@ register_model_group( DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.2", DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.2", }, + "Mistral-7B-v0.3": { + DownloadSource.DEFAULT: "mistralai/Mistral-7B-v0.3", + }, + "Mistral-7B-v0.3-Chat": { + DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.3", + }, }, template="mistral", ) @@ -656,6 +671,7 @@ register_model_group( }, "Mixtral-8x22B-v0.1-Chat": { DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-Instruct-v0.1", + DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x22B-Instruct-v0.1", }, }, template="mistral", @@ -670,6 +686,9 @@ register_model_group( "OLMo-7B": { DownloadSource.DEFAULT: "allenai/OLMo-7B-hf", }, + "OLMo-7B-Chat": { + DownloadSource.DEFAULT: "ssec-uw/OLMo-7B-Instruct-hf", + }, "OLMo-1.7-7B": { DownloadSource.DEFAULT: "allenai/OLMo-1.7-7B-hf", }, @@ -719,18 +738,23 @@ register_model_group( models={ "PaliGemma-3B-pt-224": { DownloadSource.DEFAULT: "google/paligemma-3b-pt-224", + DownloadSource.MODELSCOPE: "AI-ModelScope/paligemma-3b-pt-224", }, "PaliGemma-3B-pt-448": { DownloadSource.DEFAULT: "google/paligemma-3b-pt-448", + DownloadSource.MODELSCOPE: "AI-ModelScope/paligemma-3b-pt-448", }, "PaliGemma-3B-pt-896": { DownloadSource.DEFAULT: "google/paligemma-3b-pt-896", + DownloadSource.MODELSCOPE: "AI-ModelScope/paligemma-3b-pt-896", }, "PaliGemma-3B-mix-224": { DownloadSource.DEFAULT: "google/paligemma-3b-mix-224", + DownloadSource.MODELSCOPE: "AI-ModelScope/paligemma-3b-mix-224", }, "PaliGemma-3B-mix-448": { DownloadSource.DEFAULT: "google/paligemma-3b-mix-448", + DownloadSource.MODELSCOPE: "AI-ModelScope/paligemma-3b-mix-448", }, }, vision=True, @@ -753,14 +777,30 @@ register_model_group( register_model_group( models={ - "Phi3-3.8B-4k-Chat": { + "Phi3-4B-4k-Chat": { DownloadSource.DEFAULT: "microsoft/Phi-3-mini-4k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-4k-instruct", }, - "Phi3-3.8B-128k-Chat": { + "Phi3-4B-128k-Chat": { DownloadSource.DEFAULT: "microsoft/Phi-3-mini-128k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-128k-instruct", }, + "Phi3-7B-8k-Chat": { + DownloadSource.DEFAULT: "microsoft/Phi-3-small-8k-instruct", + DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-small-8k-instruct", + }, + "Phi3-7B-128k-Chat": { + DownloadSource.DEFAULT: "microsoft/Phi-3-small-128k-instruct", + DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-small-128k-instruct", + }, + "Phi3-14B-8k-Chat": { + DownloadSource.DEFAULT: "microsoft/Phi-3-medium-4k-instruct", + DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-4k-instruct", + }, + "Phi3-14B-128k-Chat": { + DownloadSource.DEFAULT: "microsoft/Phi-3-medium-128k-instruct", + DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-128k-instruct", + }, }, module="qkv_proj", template="phi",