Merge branch 'hiyouga:main' into main

Former-commit-id: 900631755b28692bb150a8cf39354af4e2e986c9
This commit is contained in:
Zhangchi Feng 2024-09-27 18:14:39 +08:00 committed by GitHub
commit c576b7ca32
20 changed files with 455 additions and 170 deletions

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@ -8,7 +8,6 @@ FASTAPI_ROOT_PATH=
# general # general
DISABLE_VERSION_CHECK= DISABLE_VERSION_CHECK=
FORCE_CHECK_IMPORTS= FORCE_CHECK_IMPORTS=
FORCE_TORCHRUN=
LLAMAFACTORY_VERBOSITY= LLAMAFACTORY_VERBOSITY=
USE_MODELSCOPE_HUB= USE_MODELSCOPE_HUB=
RECORD_VRAM= RECORD_VRAM=

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@ -26,7 +26,7 @@ https://github.com/user-attachments/assets/7c96b465-9df7-45f4-8053-bf03e58386d3
Choose your path: Choose your path:
- **Colab**: https://colab.research.google.com/drive/1eRTPn37ltBbYsISy9Aw2NuI2Aq5CQrD9?usp=sharing - **Colab**: https://colab.research.google.com/drive/1eRTPn37ltBbYsISy9Aw2NuI2Aq5CQrD9?usp=sharing
- **PAI-DSW**: https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory - **PAI-DSW**: [Llama3 Example](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory) | [Qwen2-VL Example](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl)
- **Local machine**: Please refer to [usage](#getting-started) - **Local machine**: Please refer to [usage](#getting-started)
- **Documentation (WIP)**: https://llamafactory.readthedocs.io/zh-cn/latest/ - **Documentation (WIP)**: https://llamafactory.readthedocs.io/zh-cn/latest/
@ -72,6 +72,8 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
## Changelog ## Changelog
[24/09/19] We support fine-tuning the **[Qwen2.5](https://qwenlm.github.io/blog/qwen2.5/)** models.
[24/08/30] We support fine-tuning the **[Qwen2-VL](https://qwenlm.github.io/blog/qwen2-vl/)** models. Thank [@simonJJJ](https://github.com/simonJJJ)'s PR. [24/08/30] We support fine-tuning the **[Qwen2-VL](https://qwenlm.github.io/blog/qwen2-vl/)** models. Thank [@simonJJJ](https://github.com/simonJJJ)'s PR.
[24/08/27] We support **[Liger Kernel](https://github.com/linkedin/Liger-Kernel)**. Try `enable_liger_kernel: true` for efficient training. [24/08/27] We support **[Liger Kernel](https://github.com/linkedin/Liger-Kernel)**. Try `enable_liger_kernel: true` for efficient training.
@ -173,7 +175,7 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
| [InternLM2/InternLM2.5](https://huggingface.co/internlm) | 7B/20B | intern2 | | [InternLM2/InternLM2.5](https://huggingface.co/internlm) | 7B/20B | intern2 |
| [Llama](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - | | [Llama](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - |
| [Llama 2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 | | [Llama 2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 |
| [Llama 3/Llama 3.1](https://huggingface.co/meta-llama) | 8B/70B | llama3 | | [Llama 3/Llama 3.1/Llama3.2](https://huggingface.co/meta-llama) | 1B/3B/8B/70B | llama3 |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | llava | | [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | llava |
| [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/13B | llava_next | | [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/13B | llava_next |
| [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/13B | llava_next_video | | [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/13B | llava_next_video |
@ -183,8 +185,8 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
| [PaliGemma](https://huggingface.co/google) | 3B | paligemma | | [PaliGemma](https://huggingface.co/google) | 3B | paligemma |
| [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - | | [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi | | [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi |
| [Qwen/Qwen1.5/Qwen2 (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/4B/7B/14B/32B/72B/110B | qwen | | [Qwen (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B | qwen2_vl | | [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B/72B | qwen2_vl |
| [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - | | [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse | | [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse |
| [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi | | [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi |

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@ -26,7 +26,7 @@ https://github.com/user-attachments/assets/e6ce34b0-52d5-4f3e-a830-592106c4c272
选择你的打开方式: 选择你的打开方式:
- **Colab**https://colab.research.google.com/drive/1d5KQtbemerlSDSxZIfAaWXhKr30QypiK?usp=sharing - **Colab**https://colab.research.google.com/drive/1d5KQtbemerlSDSxZIfAaWXhKr30QypiK?usp=sharing
- **PAI-DSW**https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory - **PAI-DSW**[Llama3 案例](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory) | [Qwen2-VL 案例](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl)
- **本地机器**:请见[如何使用](#如何使用) - **本地机器**:请见[如何使用](#如何使用)
- **入门教程**https://zhuanlan.zhihu.com/p/695287607 - **入门教程**https://zhuanlan.zhihu.com/p/695287607
- **框架文档**https://llamafactory.readthedocs.io/zh-cn/latest/ - **框架文档**https://llamafactory.readthedocs.io/zh-cn/latest/
@ -73,6 +73,8 @@ https://github.com/user-attachments/assets/e6ce34b0-52d5-4f3e-a830-592106c4c272
## 更新日志 ## 更新日志
[24/09/19] 我们支持了 **[Qwen2.5](https://qwenlm.github.io/blog/qwen2.5/)** 模型的微调。
[24/08/30] 我们支持了 **[Qwen2-VL](https://qwenlm.github.io/blog/qwen2-vl/)** 模型的微调。感谢 [@simonJJJ](https://github.com/simonJJJ) 的 PR。 [24/08/30] 我们支持了 **[Qwen2-VL](https://qwenlm.github.io/blog/qwen2-vl/)** 模型的微调。感谢 [@simonJJJ](https://github.com/simonJJJ) 的 PR。
[24/08/27] 我们支持了 **[Liger Kernel](https://github.com/linkedin/Liger-Kernel)**。请使用 `enable_liger_kernel: true` 来加速训练。 [24/08/27] 我们支持了 **[Liger Kernel](https://github.com/linkedin/Liger-Kernel)**。请使用 `enable_liger_kernel: true` 来加速训练。
@ -174,7 +176,7 @@ https://github.com/user-attachments/assets/e6ce34b0-52d5-4f3e-a830-592106c4c272
| [InternLM2/InternLM2.5](https://huggingface.co/internlm) | 7B/20B | intern2 | | [InternLM2/InternLM2.5](https://huggingface.co/internlm) | 7B/20B | intern2 |
| [Llama](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - | | [Llama](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - |
| [Llama 2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 | | [Llama 2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 |
| [Llama 3/Llama 3.1](https://huggingface.co/meta-llama) | 8B/70B | llama3 | | [Llama 3/Llama 3.1/Llama3.2](https://huggingface.co/meta-llama) | 1B/3B/8B/70B | llama3 |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | llava | | [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | llava |
| [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/13B | llava_next | | [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/13B | llava_next |
| [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/13B | llava_next_video | | [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/13B | llava_next_video |
@ -184,8 +186,8 @@ https://github.com/user-attachments/assets/e6ce34b0-52d5-4f3e-a830-592106c4c272
| [PaliGemma](https://huggingface.co/google) | 3B | paligemma | | [PaliGemma](https://huggingface.co/google) | 3B | paligemma |
| [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - | | [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi | | [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi |
| [Qwen/Qwen1.5/Qwen2 (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/4B/7B/14B/32B/72B/110B | qwen | | [Qwen (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B | qwen2_vl | | [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B/72B | qwen2_vl |
| [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - | | [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse | | [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse |
| [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi | | [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi |

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@ -12,6 +12,9 @@ ARG INSTALL_BNB=false
ARG INSTALL_VLLM=false ARG INSTALL_VLLM=false
ARG INSTALL_DEEPSPEED=false ARG INSTALL_DEEPSPEED=false
ARG INSTALL_FLASHATTN=false ARG INSTALL_FLASHATTN=false
ARG INSTALL_LIGER_KERNEL=false
ARG INSTALL_HQQ=false
ARG INSTALL_EETQ=false
ARG PIP_INDEX=https://pypi.org/simple ARG PIP_INDEX=https://pypi.org/simple
# Set the working directory # Set the working directory
@ -38,6 +41,15 @@ RUN EXTRA_PACKAGES="metrics"; \
if [ "$INSTALL_DEEPSPEED" == "true" ]; then \ if [ "$INSTALL_DEEPSPEED" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \ EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
fi; \ fi; \
if [ "$INSTALL_LIGER_KERNEL" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},liger-kernel"; \
fi; \
if [ "$INSTALL_HQQ" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},hqq"; \
fi; \
if [ "$INSTALL_EETQ" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},eetq"; \
fi; \
pip install -e ".[$EXTRA_PACKAGES]" pip install -e ".[$EXTRA_PACKAGES]"
# Rebuild flash attention # Rebuild flash attention

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@ -8,6 +8,9 @@ services:
INSTALL_VLLM: false INSTALL_VLLM: false
INSTALL_DEEPSPEED: false INSTALL_DEEPSPEED: false
INSTALL_FLASHATTN: false INSTALL_FLASHATTN: false
INSTALL_LIGER_KERNEL: false
INSTALL_HQQ: false
INSTALL_EETQ: false
PIP_INDEX: https://pypi.org/simple PIP_INDEX: https://pypi.org/simple
container_name: llamafactory container_name: llamafactory
volumes: volumes:

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@ -1,4 +1,4 @@
FROM hardandheavy/transformers-rocm:2.1.0 FROM hardandheavy/transformers-rocm:2.2.0
# Define environments # Define environments
ENV MAX_JOBS=4 ENV MAX_JOBS=4
@ -10,6 +10,8 @@ ARG INSTALL_BNB=false
ARG INSTALL_VLLM=false ARG INSTALL_VLLM=false
ARG INSTALL_DEEPSPEED=false ARG INSTALL_DEEPSPEED=false
ARG INSTALL_FLASHATTN=false ARG INSTALL_FLASHATTN=false
ARG INSTALL_LIGER_KERNEL=false
ARG INSTALL_HQQ=false
ARG PIP_INDEX=https://pypi.org/simple ARG PIP_INDEX=https://pypi.org/simple
# Set the working directory # Set the working directory
@ -36,6 +38,12 @@ RUN EXTRA_PACKAGES="metrics"; \
if [ "$INSTALL_DEEPSPEED" == "true" ]; then \ if [ "$INSTALL_DEEPSPEED" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \ EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
fi; \ fi; \
if [ "$INSTALL_LIGER_KERNEL" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},liger-kernel"; \
fi; \
if [ "$INSTALL_HQQ" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},hqq"; \
fi; \
pip install -e ".[$EXTRA_PACKAGES]" pip install -e ".[$EXTRA_PACKAGES]"
# Rebuild flash attention # Rebuild flash attention

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@ -8,6 +8,8 @@ services:
INSTALL_VLLM: false INSTALL_VLLM: false
INSTALL_DEEPSPEED: false INSTALL_DEEPSPEED: false
INSTALL_FLASHATTN: false INSTALL_FLASHATTN: false
INSTALL_LIGER_KERNEL: false
INSTALL_HQQ: false
PIP_INDEX: https://pypi.org/simple PIP_INDEX: https://pypi.org/simple
container_name: llamafactory container_name: llamafactory
volumes: volumes:

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@ -229,8 +229,9 @@ async def create_stream_chat_completion_response(
async def create_score_evaluation_response( async def create_score_evaluation_response(
request: "ScoreEvaluationRequest", chat_model: "ChatModel" request: "ScoreEvaluationRequest", chat_model: "ChatModel"
) -> "ScoreEvaluationResponse": ) -> "ScoreEvaluationResponse":
score_id = "scoreval-{}".format(uuid.uuid4().hex)
if len(request.messages) == 0: if len(request.messages) == 0:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid request") raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid request")
scores = await chat_model.aget_scores(request.messages, max_length=request.max_length) scores = await chat_model.aget_scores(request.messages, max_length=request.max_length)
return ScoreEvaluationResponse(model=request.model, scores=scores) return ScoreEvaluationResponse(id=score_id, model=request.model, scores=scores)

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@ -246,29 +246,18 @@ class HuggingfaceEngine(BaseEngine):
batch_input: List[str], batch_input: List[str],
input_kwargs: Optional[Dict[str, Any]] = {}, input_kwargs: Optional[Dict[str, Any]] = {},
) -> List[float]: ) -> List[float]:
max_length = input_kwargs.pop("max_length", None) max_length: Optional[int] = input_kwargs.pop("max_length", None)
device = getattr(model.pretrained_model, "device", "cuda") device = getattr(model.pretrained_model, "device", "cuda")
inputs = tokenizer( inputs: Dict[str, "torch.Tensor"] = tokenizer(
batch_input, batch_input,
padding=True, padding=True,
truncation=True, truncation=True,
max_length=max_length or getattr(model.config, "max_position_embeddings", 1024), max_length=max_length or getattr(model.config, "max_position_embeddings", 1024),
return_tensors="pt", return_tensors="pt",
add_special_tokens=True, add_special_tokens=False,
).to(device) ).to(device)
values: "torch.Tensor" = model(**inputs, return_dict=True, use_cache=False)[-1]
input_ids: torch.Tensor = inputs["input_ids"] scores = values.gather(dim=-1, index=(inputs["attention_mask"].sum(dim=-1, keepdim=True) - 1))
_, _, values = model(**inputs, output_hidden_states=True, return_dict=True)
if getattr(model.config, "model_type", None) == "chatglm":
values = torch.transpose(values, 0, 1)
scores = []
for i in range(input_ids.size(0)):
end_indexes = (input_ids[i] != tokenizer.pad_token_id).nonzero()
end_index = end_indexes[-1].item() if len(end_indexes) else 0
scores.append(values[i, end_index].nan_to_num().item())
return scores return scores
@override @override

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@ -113,7 +113,7 @@ class FunctionFormatter(Formatter):
functions.append((tool_call["name"], json.dumps(tool_call["arguments"], ensure_ascii=False))) functions.append((tool_call["name"], json.dumps(tool_call["arguments"], ensure_ascii=False)))
except json.JSONDecodeError: except json.JSONDecodeError:
functions = [] raise RuntimeError("Invalid JSON format in function message: {}".format(str([content]))) # flat string
elements = [] elements = []
for name, arguments in functions: for name, arguments in functions:
@ -141,7 +141,7 @@ class ToolFormatter(Formatter):
tools = json.loads(content) tools = json.loads(content)
return [self.tool_utils.tool_formatter(tools) if len(tools) != 0 else ""] return [self.tool_utils.tool_formatter(tools) if len(tools) != 0 else ""]
except json.JSONDecodeError: except json.JSONDecodeError:
return [""] raise RuntimeError("Invalid JSON format in tool description: {}".format(str([content]))) # flat string
@override @override
def extract(self, content: str) -> Union[str, List["FunctionCall"]]: def extract(self, content: str) -> Union[str, List["FunctionCall"]]:

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@ -49,6 +49,7 @@ class Template:
stop_words: List[str] stop_words: List[str]
efficient_eos: bool efficient_eos: bool
replace_eos: bool replace_eos: bool
replace_jinja_template: bool
mm_plugin: "BasePlugin" mm_plugin: "BasePlugin"
def encode_oneturn( def encode_oneturn(
@ -214,6 +215,7 @@ def _register_template(
stop_words: Sequence[str] = [], stop_words: Sequence[str] = [],
efficient_eos: bool = False, efficient_eos: bool = False,
replace_eos: bool = False, replace_eos: bool = False,
replace_jinja_template: bool = True,
mm_plugin: "BasePlugin" = get_mm_plugin(name="base"), mm_plugin: "BasePlugin" = get_mm_plugin(name="base"),
) -> None: ) -> None:
r""" r"""
@ -263,6 +265,7 @@ def _register_template(
stop_words=stop_words, stop_words=stop_words,
efficient_eos=efficient_eos, efficient_eos=efficient_eos,
replace_eos=replace_eos, replace_eos=replace_eos,
replace_jinja_template=replace_jinja_template,
mm_plugin=mm_plugin, mm_plugin=mm_plugin,
) )
@ -398,6 +401,7 @@ def get_template_and_fix_tokenizer(tokenizer: "PreTrainedTokenizer", data_args:
if num_added_tokens > 0: if num_added_tokens > 0:
logger.warning("New tokens have been added, make sure `resize_vocab` is True.") logger.warning("New tokens have been added, make sure `resize_vocab` is True.")
if template.replace_jinja_template:
try: try:
tokenizer.chat_template = _get_jinja_template(template, tokenizer) tokenizer.chat_template = _get_jinja_template(template, tokenizer)
except ValueError: except ValueError:
@ -664,6 +668,7 @@ _register_template(
format_separator=EmptyFormatter(slots=["<end_of_turn>\n"]), format_separator=EmptyFormatter(slots=["<end_of_turn>\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]), format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
efficient_eos=True, efficient_eos=True,
replace_jinja_template=False,
) )
@ -750,6 +755,7 @@ _register_template(
format_prefix=EmptyFormatter(slots=[{"bos_token"}]), format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot_id|>"], stop_words=["<|eot_id|>"],
replace_eos=True, replace_eos=True,
replace_jinja_template=False,
) )
@ -863,6 +869,7 @@ _register_template(
default_system="You are a helpful assistant.", default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"], stop_words=["<|im_end|>"],
replace_eos=True, replace_eos=True,
replace_jinja_template=False,
) )
@ -875,6 +882,7 @@ _register_template(
default_system="You are a helpful assistant.", default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"], stop_words=["<|im_end|>"],
replace_eos=True, replace_eos=True,
replace_jinja_template=False,
mm_plugin=get_mm_plugin(name="qwen2_vl", image_token="<|image_pad|>", video_token="<|video_pad|>"), mm_plugin=get_mm_plugin(name="qwen2_vl", image_token="<|image_pad|>", video_token="<|video_pad|>"),
) )

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@ -238,7 +238,7 @@ register_model_group(
"Breeze-7B": { "Breeze-7B": {
DownloadSource.DEFAULT: "MediaTek-Research/Breeze-7B-Base-v1_0", DownloadSource.DEFAULT: "MediaTek-Research/Breeze-7B-Base-v1_0",
}, },
"Breeze-7B-Chat": { "Breeze-7B-Instruct": {
DownloadSource.DEFAULT: "MediaTek-Research/Breeze-7B-Instruct-v1_0", DownloadSource.DEFAULT: "MediaTek-Research/Breeze-7B-Instruct-v1_0",
}, },
}, },
@ -319,14 +319,14 @@ register_model_group(
"CodeGemma-7B": { "CodeGemma-7B": {
DownloadSource.DEFAULT: "google/codegemma-7b", DownloadSource.DEFAULT: "google/codegemma-7b",
}, },
"CodeGemma-7B-Chat": { "CodeGemma-7B-Instruct": {
DownloadSource.DEFAULT: "google/codegemma-7b-it", DownloadSource.DEFAULT: "google/codegemma-7b-it",
DownloadSource.MODELSCOPE: "AI-ModelScope/codegemma-7b-it", DownloadSource.MODELSCOPE: "AI-ModelScope/codegemma-7b-it",
}, },
"CodeGemma-1.1-2B": { "CodeGemma-1.1-2B": {
DownloadSource.DEFAULT: "google/codegemma-1.1-2b", DownloadSource.DEFAULT: "google/codegemma-1.1-2b",
}, },
"CodeGemma-1.1-7B-Chat": { "CodeGemma-1.1-7B-Instruct": {
DownloadSource.DEFAULT: "google/codegemma-1.1-7b-it", DownloadSource.DEFAULT: "google/codegemma-1.1-7b-it",
}, },
}, },
@ -372,7 +372,7 @@ register_model_group(
DownloadSource.DEFAULT: "databricks/dbrx-base", DownloadSource.DEFAULT: "databricks/dbrx-base",
DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-base", DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-base",
}, },
"DBRX-132B-Chat": { "DBRX-132B-Instruct": {
DownloadSource.DEFAULT: "databricks/dbrx-instruct", DownloadSource.DEFAULT: "databricks/dbrx-instruct",
DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-instruct", DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-instruct",
}, },
@ -403,7 +403,7 @@ register_model_group(
DownloadSource.DEFAULT: "deepseek-ai/deepseek-math-7b-base", DownloadSource.DEFAULT: "deepseek-ai/deepseek-math-7b-base",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-math-7b-base", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-math-7b-base",
}, },
"DeepSeek-Math-7B-Chat": { "DeepSeek-Math-7B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-math-7b-instruct", DownloadSource.DEFAULT: "deepseek-ai/deepseek-math-7b-instruct",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-math-7b-instruct", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-math-7b-instruct",
}, },
@ -411,36 +411,36 @@ register_model_group(
DownloadSource.DEFAULT: "deepseek-ai/deepseek-moe-16b-base", DownloadSource.DEFAULT: "deepseek-ai/deepseek-moe-16b-base",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-moe-16b-base", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-moe-16b-base",
}, },
"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",
DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2",
},
"DeepSeek-MoE-16B-Chat": { "DeepSeek-MoE-16B-Chat": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-moe-16b-chat", DownloadSource.DEFAULT: "deepseek-ai/deepseek-moe-16b-chat",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-moe-16b-chat", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-moe-16b-chat",
}, },
"DeepSeek-MoE-16B-v2-Chat": { "DeepSeek-V2-16B-Base": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite",
DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Lite",
},
"DeepSeek-V2-236B-Base": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2",
DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2",
},
"DeepSeek-V2-16B-Chat": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite-Chat", DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite-Chat",
DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Lite-Chat", DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Lite-Chat",
}, },
"DeepSeek-MoE-236B-Chat": { "DeepSeek-V2-236B-Chat": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Chat", DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Chat",
DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Chat", DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Chat",
}, },
"DeepSeek-MoE-Coder-16B-Base": { "DeepSeek-Coder-V2-16B-Base": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Lite-Base", DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Lite-Base",
}, },
"DeepSeek-MoE-Coder-236B-Base": { "DeepSeek-Coder-V2-236B-Base": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Base", DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Base",
}, },
"DeepSeek-MoE-Coder-16B-Chat": { "DeepSeek-Coder-V2-16B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct", DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct",
}, },
"DeepSeek-MoE-Coder-236B-Chat": { "DeepSeek-Coder-V2-236B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Instruct", DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-Coder-V2-Instruct",
}, },
}, },
@ -461,14 +461,14 @@ register_model_group(
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-33b-base", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-33b-base",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-33b-base", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-33b-base",
}, },
"DeepSeekCoder-6.7B-Chat": { "DeepSeekCoder-6.7B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-6.7b-instruct", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-6.7b-instruct",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-6.7b-instruct", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-6.7b-instruct",
}, },
"DeepSeekCoder-7B-Chat": { "DeepSeekCoder-7B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-instruct-v1.5", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-instruct-v1.5",
}, },
"DeepSeekCoder-33B-Chat": { "DeepSeekCoder-33B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-33b-instruct", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-33b-instruct",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-33b-instruct", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-33b-instruct",
}, },
@ -494,11 +494,11 @@ register_model_group(
DownloadSource.DEFAULT: "tiiuae/falcon-180b", DownloadSource.DEFAULT: "tiiuae/falcon-180b",
DownloadSource.MODELSCOPE: "modelscope/falcon-180B", DownloadSource.MODELSCOPE: "modelscope/falcon-180B",
}, },
"Falcon-7B-Chat": { "Falcon-7B-Instruct": {
DownloadSource.DEFAULT: "tiiuae/falcon-7b-instruct", DownloadSource.DEFAULT: "tiiuae/falcon-7b-instruct",
DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-7b-instruct", DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-7b-instruct",
}, },
"Falcon-40B-Chat": { "Falcon-40B-Instruct": {
DownloadSource.DEFAULT: "tiiuae/falcon-40b-instruct", DownloadSource.DEFAULT: "tiiuae/falcon-40b-instruct",
DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-40b-instruct", DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-40b-instruct",
}, },
@ -521,18 +521,18 @@ register_model_group(
DownloadSource.DEFAULT: "google/gemma-7b", DownloadSource.DEFAULT: "google/gemma-7b",
DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-2b-it", DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-2b-it",
}, },
"Gemma-2B-Chat": { "Gemma-2B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-2b-it", DownloadSource.DEFAULT: "google/gemma-2b-it",
DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b", DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b",
}, },
"Gemma-7B-Chat": { "Gemma-7B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-7b-it", DownloadSource.DEFAULT: "google/gemma-7b-it",
DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b-it", DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b-it",
}, },
"Gemma-1.1-2B-Chat": { "Gemma-1.1-2B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-1.1-2b-it", DownloadSource.DEFAULT: "google/gemma-1.1-2b-it",
}, },
"Gemma-1.1-7B-Chat": { "Gemma-1.1-7B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-1.1-7b-it", DownloadSource.DEFAULT: "google/gemma-1.1-7b-it",
}, },
"Gemma-2-2B": { "Gemma-2-2B": {
@ -547,15 +547,15 @@ register_model_group(
DownloadSource.DEFAULT: "google/gemma-2-27b", DownloadSource.DEFAULT: "google/gemma-2-27b",
DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-27b", DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-27b",
}, },
"Gemma-2-2B-Chat": { "Gemma-2-2B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-2-2b-it", DownloadSource.DEFAULT: "google/gemma-2-2b-it",
DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-2b-it", DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-2b-it",
}, },
"Gemma-2-9B-Chat": { "Gemma-2-9B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-2-9b-it", DownloadSource.DEFAULT: "google/gemma-2-9b-it",
DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-9b-it", DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-9b-it",
}, },
"Gemma-2-27B-Chat": { "Gemma-2-27B-Instruct": {
DownloadSource.DEFAULT: "google/gemma-2-27b-it", DownloadSource.DEFAULT: "google/gemma-2-27b-it",
DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-27b-it", DownloadSource.MODELSCOPE: "LLM-Research/gemma-2-27b-it",
}, },
@ -764,11 +764,11 @@ register_model_group(
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-70B", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-70B",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-70B", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-70B",
}, },
"LLaMA3-8B-Chat": { "LLaMA3-8B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-8B-Instruct", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-8B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-8B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-8B-Instruct",
}, },
"LLaMA3-70B-Chat": { "LLaMA3-70B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-70B-Instruct", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-70B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-70B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-70B-Instruct",
}, },
@ -798,15 +798,15 @@ register_model_group(
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-405B", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-405B",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-405B", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-405B",
}, },
"LLaMA3.1-8B-Chat": { "LLaMA3.1-8B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-8B-Instruct", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-8B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-8B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-8B-Instruct",
}, },
"LLaMA3.1-70B-Chat": { "LLaMA3.1-70B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-70B-Instruct", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-70B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-70B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-70B-Instruct",
}, },
"LLaMA3.1-405B-Chat": { "LLaMA3.1-405B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-405B-Instruct", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-405B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-405B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-405B-Instruct",
}, },
@ -815,6 +815,29 @@ register_model_group(
) )
register_model_group(
models={
"LLaMA3.2-1B": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-1B",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-1B",
},
"LLaMA3.2-3B": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-3B",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-3B",
},
"LLaMA3.2-1B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-1B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-1B-Instruct",
},
"LLaMA3.2-3B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-3B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-3B-Instruct",
},
},
template="llama3",
)
register_model_group( register_model_group(
models={ models={
"LLaVA1.5-7B-Chat": { "LLaVA1.5-7B-Chat": {
@ -904,7 +927,7 @@ register_model_group(
DownloadSource.DEFAULT: "mistralai/Mistral-7B-v0.1", DownloadSource.DEFAULT: "mistralai/Mistral-7B-v0.1",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-v0.1", DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-v0.1",
}, },
"Mistral-7B-v0.1-Chat": { "Mistral-7B-Instruct-v0.1": {
DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.1", DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.1",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.1", DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.1",
}, },
@ -912,18 +935,18 @@ register_model_group(
DownloadSource.DEFAULT: "alpindale/Mistral-7B-v0.2-hf", DownloadSource.DEFAULT: "alpindale/Mistral-7B-v0.2-hf",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-v0.2-hf", DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-v0.2-hf",
}, },
"Mistral-7B-v0.2-Chat": { "Mistral-7B-Instruct-v0.2": {
DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.2", DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.2",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.2", DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.2",
}, },
"Mistral-7B-v0.3": { "Mistral-7B-v0.3": {
DownloadSource.DEFAULT: "mistralai/Mistral-7B-v0.3", DownloadSource.DEFAULT: "mistralai/Mistral-7B-v0.3",
}, },
"Mistral-7B-v0.3-Chat": { "Mistral-7B-Instruct-v0.3": {
DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.3", DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.3",
DownloadSource.MODELSCOPE: "LLM-Research/Mistral-7B-Instruct-v0.3", DownloadSource.MODELSCOPE: "LLM-Research/Mistral-7B-Instruct-v0.3",
}, },
"Mistral-Nemo-Chat": { "Mistral-Nemo-Instruct-2407": {
DownloadSource.DEFAULT: "mistralai/Mistral-Nemo-Instruct-2407", DownloadSource.DEFAULT: "mistralai/Mistral-Nemo-Instruct-2407",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-Nemo-Instruct-2407", DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-Nemo-Instruct-2407",
}, },
@ -938,7 +961,7 @@ register_model_group(
DownloadSource.DEFAULT: "mistralai/Mixtral-8x7B-v0.1", DownloadSource.DEFAULT: "mistralai/Mixtral-8x7B-v0.1",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x7B-v0.1", DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x7B-v0.1",
}, },
"Mixtral-8x7B-v0.1-Chat": { "Mixtral-8x7B-v0.1-Instruct": {
DownloadSource.DEFAULT: "mistralai/Mixtral-8x7B-Instruct-v0.1", DownloadSource.DEFAULT: "mistralai/Mixtral-8x7B-Instruct-v0.1",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x7B-Instruct-v0.1", DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x7B-Instruct-v0.1",
}, },
@ -946,7 +969,7 @@ register_model_group(
DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-v0.1", DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-v0.1",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x22B-v0.1", DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x22B-v0.1",
}, },
"Mixtral-8x22B-v0.1-Chat": { "Mixtral-8x22B-v0.1-Instruct": {
DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-Instruct-v0.1", DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-Instruct-v0.1",
DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x22B-Instruct-v0.1", DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x22B-Instruct-v0.1",
}, },
@ -1065,27 +1088,27 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"Phi3-4B-4k-Chat": { "Phi3-4B-4k-Instruct": {
DownloadSource.DEFAULT: "microsoft/Phi-3-mini-4k-instruct", DownloadSource.DEFAULT: "microsoft/Phi-3-mini-4k-instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-4k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-4k-instruct",
}, },
"Phi3-4B-128k-Chat": { "Phi3-4B-128k-Instruct": {
DownloadSource.DEFAULT: "microsoft/Phi-3-mini-128k-instruct", DownloadSource.DEFAULT: "microsoft/Phi-3-mini-128k-instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-128k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-128k-instruct",
}, },
"Phi3-7B-8k-Chat": { "Phi3-7B-8k-Instruct": {
DownloadSource.DEFAULT: "microsoft/Phi-3-small-8k-instruct", DownloadSource.DEFAULT: "microsoft/Phi-3-small-8k-instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-small-8k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-small-8k-instruct",
}, },
"Phi3-7B-128k-Chat": { "Phi3-7B-128k-Instruct": {
DownloadSource.DEFAULT: "microsoft/Phi-3-small-128k-instruct", DownloadSource.DEFAULT: "microsoft/Phi-3-small-128k-instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-small-128k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-small-128k-instruct",
}, },
"Phi3-14B-8k-Chat": { "Phi3-14B-8k-Instruct": {
DownloadSource.DEFAULT: "microsoft/Phi-3-medium-4k-instruct", DownloadSource.DEFAULT: "microsoft/Phi-3-medium-4k-instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-4k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-4k-instruct",
}, },
"Phi3-14B-128k-Chat": { "Phi3-14B-128k-Instruct": {
DownloadSource.DEFAULT: "microsoft/Phi-3-medium-128k-instruct", DownloadSource.DEFAULT: "microsoft/Phi-3-medium-128k-instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-128k-instruct", DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-128k-instruct",
}, },
@ -1203,10 +1226,6 @@ register_model_group(
DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B", DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B",
}, },
"Qwen1.5-Code-7B": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B",
},
"Qwen1.5-0.5B-Chat": { "Qwen1.5-0.5B-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat", DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat",
@ -1243,10 +1262,6 @@ register_model_group(
DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B-Chat", DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B-Chat",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B-Chat", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B-Chat",
}, },
"Qwen1.5-Code-7B-Chat": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat",
},
"Qwen1.5-0.5B-int8-Chat": { "Qwen1.5-0.5B-int8-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8",
@ -1307,6 +1322,14 @@ register_model_group(
DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4", DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",
}, },
"Qwen1.5-Code-7B": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B",
},
"Qwen1.5-Code-7B-Chat": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat",
},
"Qwen1.5-Code-7B-int4-Chat": { "Qwen1.5-Code-7B-int4-Chat": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat-AWQ",
@ -1334,10 +1357,82 @@ register_model_group(
DownloadSource.DEFAULT: "Qwen/Qwen2-72B", DownloadSource.DEFAULT: "Qwen/Qwen2-72B",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B", DownloadSource.MODELSCOPE: "qwen/Qwen2-72B",
}, },
"Qwen2-MoE-57B": { "Qwen2-MoE-57B-A14B": {
DownloadSource.DEFAULT: "Qwen/Qwen2-57B-A14B", DownloadSource.DEFAULT: "Qwen/Qwen2-57B-A14B",
DownloadSource.MODELSCOPE: "qwen/Qwen2-57B-A14B", DownloadSource.MODELSCOPE: "qwen/Qwen2-57B-A14B",
}, },
"Qwen2-0.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct",
},
"Qwen2-1.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct",
},
"Qwen2-7B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct",
},
"Qwen2-72B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct",
},
"Qwen2-MoE-57B-A14B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-57B-A14B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-57B-A14B-Instruct",
},
"Qwen2-0.5B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct-GPTQ-Int8",
},
"Qwen2-0.5B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct-GPTQ-Int4",
},
"Qwen2-0.5B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct-AWQ",
},
"Qwen2-1.5B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct-GPTQ-Int8",
},
"Qwen2-1.5B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct-GPTQ-Int4",
},
"Qwen2-1.5B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct-AWQ",
},
"Qwen2-7B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct-GPTQ-Int8",
},
"Qwen2-7B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct-GPTQ-Int4",
},
"Qwen2-7B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct-AWQ",
},
"Qwen2-72B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct-GPTQ-Int8",
},
"Qwen2-72B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct-GPTQ-Int4",
},
"Qwen2-72B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct-AWQ",
},
"Qwen2-57B-A14B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-57B-A14B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-57B-A14B-Instruct-GPTQ-Int4",
},
"Qwen2-Math-1.5B": { "Qwen2-Math-1.5B": {
DownloadSource.DEFAULT: "Qwen/Qwen2-Math-1.5B", DownloadSource.DEFAULT: "Qwen/Qwen2-Math-1.5B",
DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-1.5B", DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-1.5B",
@ -1350,74 +1445,18 @@ register_model_group(
DownloadSource.DEFAULT: "Qwen/Qwen2-Math-72B", DownloadSource.DEFAULT: "Qwen/Qwen2-Math-72B",
DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-72B", DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-72B",
}, },
"Qwen2-0.5B-Chat": { "Qwen2-Math-1.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct",
},
"Qwen2-1.5B-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct",
},
"Qwen2-7B-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct",
},
"Qwen2-72B-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct",
},
"Qwen2-MoE-57B-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-57B-A14B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-57B-A14B-Instruct",
},
"Qwen2-Math-1.5B-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-Math-1.5B-Instruct", DownloadSource.DEFAULT: "Qwen/Qwen2-Math-1.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-1.5B-Instruct", DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-1.5B-Instruct",
}, },
"Qwen2-Math-7B-Chat": { "Qwen2-Math-7B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-Math-7B-Instruct", DownloadSource.DEFAULT: "Qwen/Qwen2-Math-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-7B-Instruct", DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-7B-Instruct",
}, },
"Qwen2-Math-72B-Chat": { "Qwen2-Math-72B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-Math-72B-Instruct", DownloadSource.DEFAULT: "Qwen/Qwen2-Math-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-72B-Instruct", DownloadSource.MODELSCOPE: "qwen/Qwen2-Math-72B-Instruct",
}, },
"Qwen2-0.5B-int8-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct-GPTQ-Int8",
},
"Qwen2-0.5B-int4-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-0.5B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-0.5B-Instruct-AWQ",
},
"Qwen2-1.5B-int8-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct-GPTQ-Int8",
},
"Qwen2-1.5B-int4-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-1.5B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-1.5B-Instruct-AWQ",
},
"Qwen2-7B-int8-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct-GPTQ-Int8",
},
"Qwen2-7B-int4-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-7B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-7B-Instruct-AWQ",
},
"Qwen2-72B-int8-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct-GPTQ-Int8",
},
"Qwen2-72B-int4-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-72B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-72B-Instruct-AWQ",
},
"Qwen2-MoE-57B-int4-Chat": {
DownloadSource.DEFAULT: "Qwen/Qwen2-57B-A14B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-57B-A14B-Instruct-GPTQ-Int4",
},
}, },
template="qwen", template="qwen",
) )
@ -1425,30 +1464,241 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"Qwen2VL-2B-Chat": { "Qwen2.5-0.5B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-0.5B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-0.5B",
},
"Qwen2.5-1.5B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-1.5B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-1.5B",
},
"Qwen2.5-3B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-3B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-3B",
},
"Qwen2.5-7B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-7B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-7B",
},
"Qwen2.5-14B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-14B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-14B",
},
"Qwen2.5-32B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-32B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-32B",
},
"Qwen2.5-72B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-72B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-72B",
},
"Qwen2.5-0.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-0.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-0.5B-Instruct",
},
"Qwen2.5-1.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-1.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-1.5B-Instruct",
},
"Qwen2.5-3B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-3B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-3B-Instruct",
},
"Qwen2.5-7B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-7B-Instruct",
},
"Qwen2.5-14B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-14B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-14B-Instruct",
},
"Qwen2.5-32B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-32B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-32B-Instruct",
},
"Qwen2.5-72B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-72B-Instruct",
},
"Qwen2.5-0.5B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int8",
},
"Qwen2.5-0.5B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int4",
},
"Qwen2.5-0.5B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-0.5B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-0.5B-Instruct-AWQ",
},
"Qwen2.5-1.5B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-1.5B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-1.5B-Instruct-GPTQ-Int8",
},
"Qwen2.5-1.5B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-1.5B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-1.5B-Instruct-GPTQ-Int4",
},
"Qwen2.5-1.5B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-1.5B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-1.5B-Instruct-AWQ",
},
"Qwen2.5-3B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-3B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-3B-Instruct-GPTQ-Int8",
},
"Qwen2.5-3B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-3B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-3B-Instruct-GPTQ-Int4",
},
"Qwen2.5-3B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-3B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-3B-Instruct-AWQ",
},
"Qwen2.5-7B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-7B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-7B-Instruct-GPTQ-Int8",
},
"Qwen2.5-7B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-7B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-7B-Instruct-GPTQ-Int4",
},
"Qwen2.5-7B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-7B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-7B-Instruct-AWQ",
},
"Qwen2.5-14B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-14B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-14B-Instruct-GPTQ-Int8",
},
"Qwen2.5-14B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-14B-Instruct-GPTQ-Int4",
},
"Qwen2.5-14B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-14B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-14B-Instruct-AWQ",
},
"Qwen2.5-32B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-32B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-32B-Instruct-GPTQ-Int8",
},
"Qwen2.5-32B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-32B-Instruct-GPTQ-Int4",
},
"Qwen2.5-32B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-32B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-32B-Instruct-AWQ",
},
"Qwen2.5-72B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-72B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-72B-Instruct-GPTQ-Int8",
},
"Qwen2.5-72B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-72B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-72B-Instruct-GPTQ-Int4",
},
"Qwen2.5-72B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-72B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-72B-Instruct-AWQ",
},
"Qwen2.5-Coder-1.5B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Coder-1.5B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-1.5B",
},
"Qwen2.5-Coder-7B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Coder-7B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-7B",
},
"Qwen2.5-Coder-1.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Coder-1.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-1.5B-Instruct",
},
"Qwen2.5-Coder-7B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Coder-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-7B-Instruct",
},
"Qwen2.5-Math-1.5B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Math-1.5B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Math-1.5B",
},
"Qwen2.5-Math-7B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Math-7B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Math-7B",
},
"Qwen2.5-Math-72B": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Math-72B",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Math-72B",
},
"Qwen2.5-Math-1.5B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Math-1.5B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-1.5B-Instruct",
},
"Qwen2.5-Math-7B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Math-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-7B-Instruct",
},
"Qwen2.5-Math-72B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2.5-Math-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2.5-Coder-72B-Instruct",
},
},
template="qwen",
)
register_model_group(
models={
"Qwen2VL-2B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct",
}, },
"Qwen2VL-7B-Chat": { "Qwen2VL-7B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct",
}, },
"Qwen2VL-2B-int8-Chat": { "Qwen2VL-72B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct",
},
"Qwen2VL-2B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-GPTQ-Int8",
}, },
"Qwen2VL-2B-int4-Chat": { "Qwen2VL-2B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4",
},
"Qwen2VL-2B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-AWQ",
}, },
"Qwen2VL-7B-int8-Chat": { "Qwen2VL-7B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8",
}, },
"Qwen2VL-7B-int4-Chat": { "Qwen2VL-7B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4",
},
"Qwen2VL-7B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-AWQ",
}, },
"Qwen2VL-72B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-GPTQ-Int8",
},
"Qwen2VL-72B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-GPTQ-Int4",
},
"Qwen2VL-72B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-AWQ",
},
}, },
template="qwen2_vl", template="qwen2_vl",
vision=True, vision=True,
@ -1457,10 +1707,10 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"SOLAR-10.7B": { "SOLAR-10.7B-v1.0": {
DownloadSource.DEFAULT: "upstage/SOLAR-10.7B-v1.0", DownloadSource.DEFAULT: "upstage/SOLAR-10.7B-v1.0",
}, },
"SOLAR-10.7B-Chat": { "SOLAR-10.7B-Instruct-v1.0": {
DownloadSource.DEFAULT: "upstage/SOLAR-10.7B-Instruct-v1.0", DownloadSource.DEFAULT: "upstage/SOLAR-10.7B-Instruct-v1.0",
DownloadSource.MODELSCOPE: "AI-ModelScope/SOLAR-10.7B-Instruct-v1.0", DownloadSource.MODELSCOPE: "AI-ModelScope/SOLAR-10.7B-Instruct-v1.0",
}, },
@ -1635,23 +1885,23 @@ register_model_group(
DownloadSource.DEFAULT: "xverse/XVERSE-MoE-A4.2B", DownloadSource.DEFAULT: "xverse/XVERSE-MoE-A4.2B",
DownloadSource.MODELSCOPE: "xverse/XVERSE-MoE-A4.2B", DownloadSource.MODELSCOPE: "xverse/XVERSE-MoE-A4.2B",
}, },
"XVERSE-7B-int8-Chat": { "XVERSE-7B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat-GPTQ-Int8",
}, },
"XVERSE-7B-int4-Chat": { "XVERSE-7B-Chat-GPTQ-Int4": {
DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat-GPTQ-Int4", DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat-GPTQ-Int4",
DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat-GPTQ-Int4", DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat-GPTQ-Int4",
}, },
"XVERSE-13B-int8-Chat": { "XVERSE-13B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat-GPTQ-Int8",
}, },
"XVERSE-13B-int4-Chat": { "XVERSE-13B-Chat-GPTQ-Int4": {
DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat-GPTQ-Int4", DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat-GPTQ-Int4",
DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat-GPTQ-Int4", DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat-GPTQ-Int4",
}, },
"XVERSE-65B-int4-Chat": { "XVERSE-65B-Chat-GPTQ-Int4": {
DownloadSource.DEFAULT: "xverse/XVERSE-65B-Chat-GPTQ-Int4", DownloadSource.DEFAULT: "xverse/XVERSE-65B-Chat-GPTQ-Int4",
DownloadSource.MODELSCOPE: "xverse/XVERSE-65B-Chat-GPTQ-Int4", DownloadSource.MODELSCOPE: "xverse/XVERSE-65B-Chat-GPTQ-Int4",
}, },

View File

@ -26,7 +26,7 @@ import trl
from transformers.utils import is_torch_cuda_available, is_torch_npu_available from transformers.utils import is_torch_cuda_available, is_torch_npu_available
VERSION = "0.9.0" VERSION = "0.9.1.dev0"
def print_env() -> None: def print_env() -> None:

View File

@ -45,6 +45,8 @@ def configure_liger_kernel(config: "PretrainedConfig", model_args: "ModelArgumen
from liger_kernel.transformers import apply_liger_kernel_to_phi3 as apply_liger_kernel from liger_kernel.transformers import apply_liger_kernel_to_phi3 as apply_liger_kernel
elif model_type == "qwen2": elif model_type == "qwen2":
from liger_kernel.transformers import apply_liger_kernel_to_qwen2 as apply_liger_kernel from liger_kernel.transformers import apply_liger_kernel_to_qwen2 as apply_liger_kernel
elif model_type == "qwen2_vl":
from liger_kernel.transformers import apply_liger_kernel_to_qwen2_vl as apply_liger_kernel
else: else:
logger.warning("Current model does not support liger kernel.") logger.warning("Current model does not support liger kernel.")
return return

View File

@ -31,7 +31,7 @@ if TYPE_CHECKING:
from trl import AutoModelForCausalLMWithValueHead from trl import AutoModelForCausalLMWithValueHead
def get_rewards_from_server(server_url: str, messages: List[str]) -> List[torch.Tensor]: def get_rewards_from_server(server_url: str, messages: List[str]) -> List["torch.Tensor"]:
r""" r"""
Gets reward scores from the API server. Gets reward scores from the API server.
""" """
@ -66,7 +66,7 @@ def replace_model(model: "AutoModelForCausalLMWithValueHead", target: Literal["d
v_head_layer.bias.data = model.get_buffer("{}_head_bias".format(target)).detach().clone().to(device) v_head_layer.bias.data = model.get_buffer("{}_head_bias".format(target)).detach().clone().to(device)
def dump_layernorm(model: "PreTrainedModel") -> Dict[str, torch.Tensor]: def dump_layernorm(model: "PreTrainedModel") -> Dict[str, "torch.Tensor"]:
r""" r"""
Dumps the layernorm parameters in the model. The model is already unwrapped (and gathered). Dumps the layernorm parameters in the model. The model is already unwrapped (and gathered).
""" """
@ -79,7 +79,7 @@ def dump_layernorm(model: "PreTrainedModel") -> Dict[str, torch.Tensor]:
return layer_norm_params return layer_norm_params
def restore_layernorm(model: "PreTrainedModel", layernorm_params: Optional[Dict[str, torch.Tensor]] = None) -> None: def restore_layernorm(model: "PreTrainedModel", layernorm_params: Optional[Dict[str, "torch.Tensor"]] = None) -> None:
r""" r"""
Restores the layernorm parameters in the model. The model is already unwrapped (and gathered). Restores the layernorm parameters in the model. The model is already unwrapped (and gathered).
""" """

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@ -392,7 +392,7 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
""" """
if self.finetuning_args.reward_model_type == "api": if self.finetuning_args.reward_model_type == "api":
token_ids = [torch.cat((q, r), dim=-1).tolist() for q, r in zip(queries, responses)] token_ids = [torch.cat((q, r), dim=-1).tolist() for q, r in zip(queries, responses)]
messages = self.tokenizer.batch_decode(token_ids, skip_special_tokens=True) messages = self.tokenizer.batch_decode(token_ids, skip_special_tokens=False)
return get_rewards_from_server(self.reward_model, messages) return get_rewards_from_server(self.reward_model, messages)
batch: Dict[str, "torch.Tensor"] = self.prepare_model_inputs(queries, responses) batch: Dict[str, "torch.Tensor"] = self.prepare_model_inputs(queries, responses)
@ -405,7 +405,7 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
reward_model = self.reward_model reward_model = self.reward_model
with unwrap_model_for_generation(reward_model, self.accelerator), self.amp_context: # support bf16 with unwrap_model_for_generation(reward_model, self.accelerator), self.amp_context: # support bf16
_, _, values = reward_model(**batch, return_dict=True, use_cache=False) values: "torch.Tensor" = reward_model(**batch, return_dict=True, use_cache=False)[-1]
if self.finetuning_args.reward_model_type == "lora": if self.finetuning_args.reward_model_type == "lora":
replace_model(unwrapped_model, target="default") replace_model(unwrapped_model, target="default")

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@ -137,8 +137,13 @@ def get_template(model_name: str) -> str:
r""" r"""
Gets the template name if the model is a chat model. Gets the template name if the model is a chat model.
""" """
if model_name and model_name.endswith("Chat") and get_prefix(model_name) in DEFAULT_TEMPLATE: if (
model_name
and any(suffix in model_name for suffix in ("-Chat", "-Instruct"))
and get_prefix(model_name) in DEFAULT_TEMPLATE
):
return DEFAULT_TEMPLATE[get_prefix(model_name)] return DEFAULT_TEMPLATE[get_prefix(model_name)]
return "default" return "default"

View File

@ -19,6 +19,7 @@ import pytest
from transformers import AutoTokenizer from transformers import AutoTokenizer
from llamafactory.data import get_template_and_fix_tokenizer from llamafactory.data import get_template_and_fix_tokenizer
from llamafactory.data.template import _get_jinja_template
from llamafactory.hparams import DataArguments from llamafactory.hparams import DataArguments
@ -117,7 +118,8 @@ def test_encode_multiturn(use_fast: bool):
def test_jinja_template(use_fast: bool): def test_jinja_template(use_fast: bool):
tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA, use_fast=use_fast) tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA, use_fast=use_fast)
ref_tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA, use_fast=use_fast) ref_tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA, use_fast=use_fast)
get_template_and_fix_tokenizer(tokenizer, DataArguments(template="llama3")) template = get_template_and_fix_tokenizer(tokenizer, DataArguments(template="llama3"))
tokenizer.chat_template = _get_jinja_template(template, tokenizer) # llama3 template no replace
assert tokenizer.chat_template != ref_tokenizer.chat_template assert tokenizer.chat_template != ref_tokenizer.chat_template
assert tokenizer.apply_chat_template(MESSAGES) == ref_tokenizer.apply_chat_template(MESSAGES) assert tokenizer.apply_chat_template(MESSAGES) == ref_tokenizer.apply_chat_template(MESSAGES)