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Merge pull request #5574 from BUAADreamer/main

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support llava-next(video)/video-llava

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hoshi-hiyouga 2024-09-30 00:22:43 +08:00 committed by GitHub
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58
README.md
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@ -162,34 +162,36 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
## Supported Models ## Supported Models
| Model | Model size | Template | | Model | Model size | Template |
| ----------------------------------------------------------------- | -------------------------------- | --------- | | ----------------------------------------------------------------- | -------------------------------- | ---------------- |
| [Baichuan 2](https://huggingface.co/baichuan-inc) | 7B/13B | baichuan2 | | [Baichuan 2](https://huggingface.co/baichuan-inc) | 7B/13B | baichuan2 |
| [BLOOM/BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - | | [BLOOM/BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - |
| [ChatGLM3](https://huggingface.co/THUDM) | 6B | chatglm3 | | [ChatGLM3](https://huggingface.co/THUDM) | 6B | chatglm3 |
| [Command R](https://huggingface.co/CohereForAI) | 35B/104B | cohere | | [Command R](https://huggingface.co/CohereForAI) | 35B/104B | cohere |
| [DeepSeek (Code/MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | deepseek | | [DeepSeek (Code/MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | deepseek |
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon | | [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon |
| [Gemma/Gemma 2/CodeGemma](https://huggingface.co/google) | 2B/7B/9B/27B | gemma | | [Gemma/Gemma 2/CodeGemma](https://huggingface.co/google) | 2B/7B/9B/27B | gemma |
| [GLM-4](https://huggingface.co/THUDM) | 9B | glm4 | | [GLM-4](https://huggingface.co/THUDM) | 9B | glm4 |
| [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 3-3.2](https://huggingface.co/meta-llama) | 1B/3B/8B/70B | llama3 | | [Llama 3-3.2](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 |
| [MiniCPM](https://huggingface.co/openbmb) | 1B/2B/4B | cpm/cpm3 | | [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/8B/13B/34B/72B/110B | llava_next |
| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | mistral | | [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/34B | llava_next_video |
| [OLMo](https://huggingface.co/allenai) | 1B/7B | - | | [MiniCPM](https://huggingface.co/openbmb) | 1B/2B/4B | cpm/cpm3 |
| [PaliGemma](https://huggingface.co/google) | 3B | paligemma | | [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | mistral |
| [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - | | [OLMo](https://huggingface.co/allenai) | 1B/7B | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi | | [PaliGemma](https://huggingface.co/google) | 3B | paligemma |
| [Qwen (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen | | [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - |
| [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B/72B | qwen2_vl | | [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi |
| [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - | | [Qwen (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse | | [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B/72B | qwen2_vl |
| [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi | | [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | yi_vl | | [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse |
| [Yuan 2](https://huggingface.co/IEITYuan) | 2B/51B/102B | yuan | | [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | yi_vl |
| [Yuan 2](https://huggingface.co/IEITYuan) | 2B/51B/102B | yuan |
> [!NOTE] > [!NOTE]
> For the "base" models, the `template` argument can be chosen from `default`, `alpaca`, `vicuna` etc. But make sure to use the **corresponding template** for the "instruct/chat" models. > For the "base" models, the `template` argument can be chosen from `default`, `alpaca`, `vicuna` etc. But make sure to use the **corresponding template** for the "instruct/chat" models.

58
README_zh.md
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@ -163,34 +163,36 @@ https://github.com/user-attachments/assets/e6ce34b0-52d5-4f3e-a830-592106c4c272
## 模型 ## 模型
| 模型名 | 模型大小 | Template | | 模型名 | 模型大小 | Template |
| ----------------------------------------------------------------- | -------------------------------- | --------- | | ----------------------------------------------------------------- | -------------------------------- | ---------------- |
| [Baichuan 2](https://huggingface.co/baichuan-inc) | 7B/13B | baichuan2 | | [Baichuan 2](https://huggingface.co/baichuan-inc) | 7B/13B | baichuan2 |
| [BLOOM/BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - | | [BLOOM/BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - |
| [ChatGLM3](https://huggingface.co/THUDM) | 6B | chatglm3 | | [ChatGLM3](https://huggingface.co/THUDM) | 6B | chatglm3 |
| [Command R](https://huggingface.co/CohereForAI) | 35B/104B | cohere | | [Command R](https://huggingface.co/CohereForAI) | 35B/104B | cohere |
| [DeepSeek (Code/MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | deepseek | | [DeepSeek (Code/MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | deepseek |
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon | | [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon |
| [Gemma/Gemma 2/CodeGemma](https://huggingface.co/google) | 2B/7B/9B/27B | gemma | | [Gemma/Gemma 2/CodeGemma](https://huggingface.co/google) | 2B/7B/9B/27B | gemma |
| [GLM-4](https://huggingface.co/THUDM) | 9B | glm4 | | [GLM-4](https://huggingface.co/THUDM) | 9B | glm4 |
| [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 3-3.2](https://huggingface.co/meta-llama) | 1B/3B/8B/70B | llama3 | | [Llama 3-3.2](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 |
| [MiniCPM](https://huggingface.co/openbmb) | 1B/2B/4B | cpm/cpm3 | | [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/8B/13B/34B/72B/110B | llava_next |
| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | mistral | | [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/34B | llava_next_video |
| [OLMo](https://huggingface.co/allenai) | 1B/7B | - | | [MiniCPM](https://huggingface.co/openbmb) | 1B/2B/4B | cpm/cpm3 |
| [PaliGemma](https://huggingface.co/google) | 3B | paligemma | | [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | mistral |
| [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - | | [OLMo](https://huggingface.co/allenai) | 1B/7B | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi | | [PaliGemma](https://huggingface.co/google) | 3B | paligemma |
| [Qwen (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen | | [Phi-1.5/Phi-2](https://huggingface.co/microsoft) | 1.3B/2.7B | - |
| [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B/72B | qwen2_vl | | [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi |
| [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - | | [Qwen (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse | | [Qwen2-VL](https://huggingface.co/Qwen) | 2B/7B/72B | qwen2_vl |
| [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi | | [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | yi_vl | | [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse |
| [Yuan 2](https://huggingface.co/IEITYuan) | 2B/51B/102B | yuan | | [Yi/Yi-1.5 (Code)](https://huggingface.co/01-ai) | 1.5B/6B/9B/34B | yi |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | yi_vl |
| [Yuan 2](https://huggingface.co/IEITYuan) | 2B/51B/102B | yuan |
> [!NOTE] > [!NOTE]
> 对于所有“基座”（Base）模型，`template` 参数可以是 `default`, `alpaca`, `vicuna` 等任意值。但“对话”（Instruct/Chat）模型请务必使用**对应的模板**。 > 对于所有“基座”（Base）模型，`template` 参数可以是 `default`, `alpaca`, `vicuna` 等任意值。但“对话”（Instruct/Chat）模型请务必使用**对应的模板**。

1
requirements.txt
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@ -19,3 +19,4 @@ fire
packaging packaging
pyyaml pyyaml
numpy<2.0.0 numpy<2.0.0
av

198
src/llamafactory/data/mm_plugin.py
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@ -4,6 +4,7 @@ from io import BytesIO
from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple, TypedDict, Union from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple, TypedDict, Union
import numpy as np import numpy as np
from transformers.image_utils import get_image_size, to_numpy_array
from typing_extensions import override from typing_extensions import override
from ..extras.constants import IGNORE_INDEX, IMAGE_PLACEHOLDER, VIDEO_PLACEHOLDER from ..extras.constants import IGNORE_INDEX, IMAGE_PLACEHOLDER, VIDEO_PLACEHOLDER
@ -157,6 +158,7 @@ class BasePlugin:
It holds num_patches == torch.prod(image_grid_thw) It holds num_patches == torch.prod(image_grid_thw)
""" """
image_processor: "BaseImageProcessor" = getattr(processor, "image_processor") image_processor: "BaseImageProcessor" = getattr(processor, "image_processor")
video_processor: "BaseImageProcessor" = getattr(processor, "video_processor", image_processor)
input_dict = {"images": None} # default key input_dict = {"images": None} # default key
if len(images) != 0: if len(images) != 0:
images = self._regularize_images( images = self._regularize_images(
@ -174,10 +176,16 @@ class BasePlugin:
) )
input_dict["videos"] = videos input_dict["videos"] = videos
if input_dict.get("images", None) is not None or input_dict.get("videos", None) is not None: mm_inputs = {}
return image_processor(**input_dict, return_tensors="pt") if image_processor != video_processor:
else: if input_dict.get("images") is not None:
return {} mm_inputs.update(image_processor(input_dict["images"], return_tensors="pt"))
if input_dict.get("videos") is not None:
mm_inputs.update(video_processor(input_dict["videos"], return_tensors="pt"))
elif input_dict.get("images") is not None or input_dict.get("videos") is not None: # same processor (qwen2-vl)
mm_inputs.update(image_processor(**input_dict, return_tensors="pt"))
return mm_inputs
def process_messages( def process_messages(
self, self,
@ -263,6 +271,122 @@ class LlavaPlugin(BasePlugin):
return self._get_mm_inputs(images, videos, processor) return self._get_mm_inputs(images, videos, processor)
class LlavaNextPlugin(BasePlugin):
@override
def process_messages(
self,
messages: Sequence[Dict[str, str]],
images: Sequence["ImageInput"],
videos: Sequence["VideoInput"],
processor: Optional["ProcessorMixin"],
) -> List[Dict[str, str]]:
self._validate_input(images, videos)
num_image_tokens = 0
messages = deepcopy(messages)
mm_inputs = self._get_mm_inputs(images, videos, processor)
if "image_sizes" in mm_inputs:
image_sizes = iter(mm_inputs["image_sizes"])
if "pixel_values" in mm_inputs:
height, width = get_image_size(to_numpy_array(mm_inputs["pixel_values"][0][0]))
for message in messages:
content = message["content"]
while self.image_token in content:
image_size = next(image_sizes)
orig_height, orig_width = image_size
image_seqlen = processor._get_number_of_features(orig_height, orig_width, height, width)
if processor.vision_feature_select_strategy == "default":
image_seqlen -= 1
num_image_tokens += 1
content = content.replace(self.image_token, "{{image}}" * image_seqlen, 1)
message["content"] = content.replace("{{image}}", self.image_token)
if len(images) != num_image_tokens:
raise ValueError("The number of images does not match the number of {} tokens".format(IMAGE_PLACEHOLDER))
return messages
@override
def get_mm_inputs(
self,
images: Sequence["ImageInput"],
videos: Sequence["VideoInput"],
imglens: Sequence[int],
vidlens: Sequence[int],
seqlens: Sequence[int],
processor: Optional["ProcessorMixin"],
) -> Dict[str, Union[List[int], "torch.Tensor"]]:
self._validate_input(images, videos)
res = self._get_mm_inputs(images, videos, processor)
return res
class LlavaNextVideoPlugin(BasePlugin):
@override
def process_messages(
self,
messages: Sequence[Dict[str, str]],
images: Sequence["ImageInput"],
videos: Sequence["VideoInput"],
processor: Optional["ProcessorMixin"],
) -> List[Dict[str, str]]:
self._validate_input(images, videos)
num_image_tokens = 0
num_video_tokens = 0
messages = deepcopy(messages)
mm_inputs = self._get_mm_inputs(images, videos, processor)
if "pixel_values" in mm_inputs:
image_sizes = iter(mm_inputs["image_sizes"])
height, width = get_image_size(to_numpy_array(mm_inputs["pixel_values"][0][0]))
for message in messages:
content = message["content"]
while self.image_token in content:
image_size = next(image_sizes)
orig_height, orig_width = image_size
image_seqlen = processor._get_number_of_features(orig_height, orig_width, height, width)
if processor.vision_feature_select_strategy == "default":
image_seqlen -= 1
num_image_tokens += 1
content = content.replace(self.image_token, "{{image}}" * image_seqlen, 1)
message["content"] = content.replace("{{image}}", self.image_token)
if "pixel_values_videos" in mm_inputs:
pixel_values_video = to_numpy_array(mm_inputs.get("pixel_values_videos")[0])
height, width = get_image_size(pixel_values_video[0])
num_frames = pixel_values_video.shape[0] # frame dim is always after batch dim
image_seqlen = (height // processor.patch_size) * (width // processor.patch_size)
video_seqlen = image_seqlen // 4 * num_frames # divide by 4 needed for avg pooling layer
for message in messages:
content = message["content"]
while self.video_token in content:
num_video_tokens += 1
content = content.replace(self.video_token, "{{video}}", 1)
message["content"] = content.replace("{{video}}", self.video_token * video_seqlen)
if len(images) != num_image_tokens:
raise ValueError("The number of images does not match the number of {} tokens".format(IMAGE_PLACEHOLDER))
if len(videos) != num_video_tokens:
raise ValueError("The number of videos does not match the number of {} tokens".format(IMAGE_PLACEHOLDER))
return messages
@override
def get_mm_inputs(
self,
images: Sequence["ImageInput"],
videos: Sequence["VideoInput"],
imglens: Sequence[int],
vidlens: Sequence[int],
seqlens: Sequence[int],
processor: Optional["ProcessorMixin"],
) -> Dict[str, Union[List[int], "torch.Tensor"]]:
self._validate_input(images, videos)
return self._get_mm_inputs(images, videos, processor)
class PaliGemmaPlugin(BasePlugin): class PaliGemmaPlugin(BasePlugin):
@override @override
def process_messages( def process_messages(
@ -417,11 +541,77 @@ class Qwen2vlPlugin(BasePlugin):
return self._get_mm_inputs(images, videos, processor) return self._get_mm_inputs(images, videos, processor)
class VideoLlavaPlugin(BasePlugin):
@override
def process_messages(
self,
messages: Sequence[Dict[str, str]],
images: Sequence["ImageInput"],
videos: Sequence["VideoInput"],
processor: Optional["ProcessorMixin"],
) -> List[Dict[str, str]]:
self._validate_input(images, videos)
num_image_tokens = 0
num_video_tokens = 0
messages = deepcopy(messages)
mm_inputs = self._get_mm_inputs(images, videos, processor)
num_frames = 0
exist_images = "pixel_values_images" in mm_inputs
exist_videos = "pixel_values_videos" in mm_inputs
if exist_videos or exist_images:
if exist_images:
height, width = get_image_size(to_numpy_array(mm_inputs.get("pixel_values_images")[0]))
num_frames = 1
if exist_videos:
pixel_values_video = to_numpy_array(mm_inputs.get("pixel_values_videos")[0])
height, width = get_image_size(pixel_values_video[0])
num_frames = pixel_values_video.shape[0] # frame dim is always after batch dim
image_seqlen = (height // processor.patch_size) * (width // processor.patch_size) + 1
video_seqlen = image_seqlen * num_frames
if processor.vision_feature_select_strategy == "default":
image_seqlen -= 1
for message in messages:
content = message["content"]
while self.image_token in content:
num_image_tokens += 1
content = content.replace(self.image_token, "{{image}}", 1)
while self.video_token in content:
num_video_tokens += 1
content = content.replace(self.video_token, "{{video}}", 1)
content = content.replace("{{image}}", self.image_token * image_seqlen)
message["content"] = content.replace("{{video}}", self.video_token * video_seqlen)
if len(images) != num_image_tokens:
raise ValueError("The number of images does not match the number of {} tokens".format(self.image_token))
if len(videos) != num_video_tokens:
raise ValueError("The number of videos does not match the number of {} tokens".format(self.video_token))
return messages
@override
def get_mm_inputs(
self,
images: Sequence["ImageInput"],
videos: Sequence["VideoInput"],
imglens: Sequence[int],
vidlens: Sequence[int],
seqlens: Sequence[int],
processor: Optional["ProcessorMixin"],
) -> Dict[str, Union[List[int], "torch.Tensor"]]:
self._validate_input(images, videos)
return self._get_mm_inputs(images, videos, processor)
PLUGINS = { PLUGINS = {
"base": BasePlugin, "base": BasePlugin,
"llava": LlavaPlugin, "llava": LlavaPlugin,
"llava_next": LlavaNextPlugin,
"llava_next_video": LlavaNextVideoPlugin,
"paligemma": PaliGemmaPlugin, "paligemma": PaliGemmaPlugin,
"qwen2_vl": Qwen2vlPlugin, "qwen2_vl": Qwen2vlPlugin,
"video_llava": VideoLlavaPlugin,
} }

112
src/llamafactory/data/template.py
View File

@ -760,6 +760,107 @@ _register_template(
) )
_register_template(
name="llava_next",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_system=(
"A chat between a curious user and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the user's questions."
),
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
_register_template(
name="llava_next_llama3",
format_user=StringFormatter(
slots=[
(
"<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_system=StringFormatter(slots=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
format_observation=StringFormatter(
slots=[
(
"<|start_header_id|>tool<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot_id|>"],
replace_eos=True,
replace_jinja_template=False,
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
_register_template(
name="llava_next_mistral",
format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
_register_template(
name="llava_next_qwen",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_separator=EmptyFormatter(slots=["\n"]),
default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"],
replace_eos=True,
replace_jinja_template=False,
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
_register_template(
name="llava_next_yi",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_separator=EmptyFormatter(slots=["\n"]),
stop_words=["<|im_end|>"],
replace_eos=True,
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
_register_template(
name="llava_next_video",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_system=(
"A chat between a curious user and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the user's questions."
),
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
)
_register_template(
name="llava_next_video_mistral",
format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
)
_register_template(
name="llava_next_video_yi",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_separator=EmptyFormatter(slots=["\n"]),
stop_words=["<|im_end|>"],
replace_eos=True,
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
)
_register_template( _register_template(
name="mistral", name="mistral",
format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]), format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]),
@ -906,6 +1007,17 @@ _register_template(
) )
_register_template(
name="video_llava",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_system=(
"A chat between a curious user and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the user's questions."
),
mm_plugin=get_mm_plugin(name="video_llava", image_token="<image>", video_token="<video>"),
)
_register_template( _register_template(
name="xuanyuan", name="xuanyuan",
format_user=StringFormatter(slots=["Human: {{content}} Assistant:"]), format_user=StringFormatter(slots=["Human: {{content}} Assistant:"]),

366
src/llamafactory/extras/constants.py
View File

@ -114,17 +114,12 @@ def register_model_group(
template: Optional[str] = None, template: Optional[str] = None,
vision: bool = False, vision: bool = False,
) -> None: ) -> None:
prefix = None
for name, path in models.items(): for name, path in models.items():
if prefix is None:
prefix = name.split("-")[0]
else:
assert prefix == name.split("-")[0], "prefix should be identical."
SUPPORTED_MODELS[name] = path SUPPORTED_MODELS[name] = path
if template is not None: if template is not None and any(suffix in name for suffix in ("-Chat", "-Instruct")):
DEFAULT_TEMPLATE[prefix] = template DEFAULT_TEMPLATE[name] = template
if vision: if vision:
VISION_MODELS.add(prefix) VISION_MODELS.add(name)
register_model_group( register_model_group(
@ -274,27 +269,27 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"ChineseLLaMA2-1.3B": { "Chinese-Llama-2-1.3B": {
DownloadSource.DEFAULT: "hfl/chinese-llama-2-1.3b", DownloadSource.DEFAULT: "hfl/chinese-llama-2-1.3b",
DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-1.3b", DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-1.3b",
}, },
"ChineseLLaMA2-7B": { "Chinese-Llama-2-7B": {
DownloadSource.DEFAULT: "hfl/chinese-llama-2-7b", DownloadSource.DEFAULT: "hfl/chinese-llama-2-7b",
DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-7b", DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-7b",
}, },
"ChineseLLaMA2-13B": { "Chinese-Llama-2-13B": {
DownloadSource.DEFAULT: "hfl/chinese-llama-2-13b", DownloadSource.DEFAULT: "hfl/chinese-llama-2-13b",
DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-13b", DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-13b",
}, },
"ChineseLLaMA2-1.3B-Chat": { "Chinese-Alpaca-2-1.3B-Chat": {
DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-1.3b", DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-1.3b",
DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-1.3b", DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-1.3b",
}, },
"ChineseLLaMA2-7B-Chat": { "Chinese-Alpaca-2-7B-Chat": {
DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-7b", DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-7b",
DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-7b", DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-7b",
}, },
"ChineseLLaMA2-13B-Chat": { "Chinese-Alpaca-2-13B-Chat": {
DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-13b", DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-13b",
DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-13b", DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-13b",
}, },
@ -450,25 +445,25 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"DeepSeekCoder-6.7B-Base": { "DeepSeek-Coder-6.7B-Base": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-6.7b-base", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-6.7b-base",
DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-6.7b-base", DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-6.7b-base",
}, },
"DeepSeekCoder-7B-Base": { "DeepSeek-Coder-7B-Base": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-base-v1.5", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-base-v1.5",
}, },
"DeepSeekCoder-33B-Base": { "DeepSeek-Coder-33B-Base": {
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-Instruct": { "DeepSeek-Coder-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-Instruct": { "DeepSeek-Coder-7B-Instruct": {
DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-instruct-v1.5", DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-instruct-v1.5",
}, },
"DeepSeekCoder-33B-Instruct": { "DeepSeek-Coder-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",
}, },
@ -624,13 +619,6 @@ register_model_group(
DownloadSource.DEFAULT: "internlm/internlm2-chat-20b", DownloadSource.DEFAULT: "internlm/internlm2-chat-20b",
DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-chat-20b", DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-chat-20b",
}, },
},
template="intern2",
)
register_model_group(
models={
"InternLM2.5-1.8B": { "InternLM2.5-1.8B": {
DownloadSource.DEFAULT: "internlm/internlm2_5-1_8b", DownloadSource.DEFAULT: "internlm/internlm2_5-1_8b",
DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2_5-1_8b", DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2_5-1_8b",
@ -686,19 +674,19 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"LLaMA-7B": { "Llama-7B": {
DownloadSource.DEFAULT: "huggyllama/llama-7b", DownloadSource.DEFAULT: "huggyllama/llama-7b",
DownloadSource.MODELSCOPE: "skyline2006/llama-7b", DownloadSource.MODELSCOPE: "skyline2006/llama-7b",
}, },
"LLaMA-13B": { "Llama-13B": {
DownloadSource.DEFAULT: "huggyllama/llama-13b", DownloadSource.DEFAULT: "huggyllama/llama-13b",
DownloadSource.MODELSCOPE: "skyline2006/llama-13b", DownloadSource.MODELSCOPE: "skyline2006/llama-13b",
}, },
"LLaMA-30B": { "Llama-30B": {
DownloadSource.DEFAULT: "huggyllama/llama-30b", DownloadSource.DEFAULT: "huggyllama/llama-30b",
DownloadSource.MODELSCOPE: "skyline2006/llama-30b", DownloadSource.MODELSCOPE: "skyline2006/llama-30b",
}, },
"LLaMA-65B": { "Llama-65B": {
DownloadSource.DEFAULT: "huggyllama/llama-65b", DownloadSource.DEFAULT: "huggyllama/llama-65b",
DownloadSource.MODELSCOPE: "skyline2006/llama-65b", DownloadSource.MODELSCOPE: "skyline2006/llama-65b",
}, },
@ -708,27 +696,27 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"LLaMA2-7B": { "Llama-2-7B": {
DownloadSource.DEFAULT: "meta-llama/Llama-2-7b-hf", DownloadSource.DEFAULT: "meta-llama/Llama-2-7b-hf",
DownloadSource.MODELSCOPE: "modelscope/Llama-2-7b-ms", DownloadSource.MODELSCOPE: "modelscope/Llama-2-7b-ms",
}, },
"LLaMA2-13B": { "Llama-2-13B": {
DownloadSource.DEFAULT: "meta-llama/Llama-2-13b-hf", DownloadSource.DEFAULT: "meta-llama/Llama-2-13b-hf",
DownloadSource.MODELSCOPE: "modelscope/Llama-2-13b-ms", DownloadSource.MODELSCOPE: "modelscope/Llama-2-13b-ms",
}, },
"LLaMA2-70B": { "Llama-2-70B": {
DownloadSource.DEFAULT: "meta-llama/Llama-2-70b-hf", DownloadSource.DEFAULT: "meta-llama/Llama-2-70b-hf",
DownloadSource.MODELSCOPE: "modelscope/Llama-2-70b-ms", DownloadSource.MODELSCOPE: "modelscope/Llama-2-70b-ms",
}, },
"LLaMA2-7B-Chat": { "Llama-2-7B-Chat": {
DownloadSource.DEFAULT: "meta-llama/Llama-2-7b-chat-hf", DownloadSource.DEFAULT: "meta-llama/Llama-2-7b-chat-hf",
DownloadSource.MODELSCOPE: "modelscope/Llama-2-7b-chat-ms", DownloadSource.MODELSCOPE: "modelscope/Llama-2-7b-chat-ms",
}, },
"LLaMA2-13B-Chat": { "Llama-2-13B-Chat": {
DownloadSource.DEFAULT: "meta-llama/Llama-2-13b-chat-hf", DownloadSource.DEFAULT: "meta-llama/Llama-2-13b-chat-hf",
DownloadSource.MODELSCOPE: "modelscope/Llama-2-13b-chat-ms", DownloadSource.MODELSCOPE: "modelscope/Llama-2-13b-chat-ms",
}, },
"LLaMA2-70B-Chat": { "Llama-2-70B-Chat": {
DownloadSource.DEFAULT: "meta-llama/Llama-2-70b-chat-hf", DownloadSource.DEFAULT: "meta-llama/Llama-2-70b-chat-hf",
DownloadSource.MODELSCOPE: "modelscope/Llama-2-70b-chat-ms", DownloadSource.MODELSCOPE: "modelscope/Llama-2-70b-chat-ms",
}, },
@ -739,80 +727,74 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"LLaMA3-8B": { "Llama-3-8B": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-8B", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-8B",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-8B", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-8B",
}, },
"LLaMA3-70B": { "Llama-3-70B": {
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-Instruct": { "Llama-3-8B-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-Instruct": { "Llama-3-70B-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",
}, },
"LLaMA3-8B-Chinese-Chat": { "Llama-3-8B-Chinese-Chat": {
DownloadSource.DEFAULT: "shenzhi-wang/Llama3-8B-Chinese-Chat", DownloadSource.DEFAULT: "shenzhi-wang/Llama3-8B-Chinese-Chat",
DownloadSource.MODELSCOPE: "LLM-Research/Llama3-8B-Chinese-Chat", DownloadSource.MODELSCOPE: "LLM-Research/Llama3-8B-Chinese-Chat",
}, },
"LLaMA3-70B-Chinese-Chat": { "Llama-3-70B-Chinese-Chat": {
DownloadSource.DEFAULT: "shenzhi-wang/Llama3-70B-Chinese-Chat", DownloadSource.DEFAULT: "shenzhi-wang/Llama3-70B-Chinese-Chat",
}, },
}, "Llama-3.1-8B": {
template="llama3",
)
register_model_group(
models={
"LLaMA3.1-8B": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-8B", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-8B",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-8B", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-8B",
}, },
"LLaMA3.1-70B": { "Llama-3.1-70B": {
DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-70B", DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3.1-70B",
DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-70B", DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3.1-70B",
}, },
"LLaMA3.1-405B": { "Llama-3.1-405B": {
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-Instruct": { "Llama-3.1-8B-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-Instruct": { "Llama-3.1-70B-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-Instruct": { "Llama-3.1-405B-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",
}, },
}, "Llama-3.1-8B-Chinese-Chat": {
template="llama3", DownloadSource.DEFAULT: "shenzhi-wang/Llama3.1-8B-Chinese-Chat",
) DownloadSource.MODELSCOPE: "XD_AI/Llama3.1-8B-Chinese-Chat",
},
"Llama-3.1-70B-Chinese-Chat": {
register_model_group( DownloadSource.DEFAULT: "shenzhi-wang/Llama3.1-70B-Chinese-Chat",
models={ DownloadSource.MODELSCOPE: "XD_AI/Llama3.1-70B-Chinese-Chat",
"LLaMA3.2-1B": { },
"Llama-3.2-1B": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-1B", DownloadSource.DEFAULT: "meta-llama/Llama-3.2-1B",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-1B", DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-1B",
}, },
"LLaMA3.2-3B": { "Llama-3.2-3B": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-3B", DownloadSource.DEFAULT: "meta-llama/Llama-3.2-3B",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-3B", DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-3B",
}, },
"LLaMA3.2-1B-Instruct": { "Llama-3.2-1B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-1B-Instruct", DownloadSource.DEFAULT: "meta-llama/Llama-3.2-1B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-1B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-1B-Instruct",
}, },
"LLaMA3.2-3B-Instruct": { "Llama-3.2-3B-Instruct": {
DownloadSource.DEFAULT: "meta-llama/Llama-3.2-3B-Instruct", DownloadSource.DEFAULT: "meta-llama/Llama-3.2-3B-Instruct",
DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-3B-Instruct", DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-3B-Instruct",
}, },
@ -823,11 +805,13 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"LLaVA1.5-7B-Chat": { "LLaVA-1.5-7B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-1.5-7b-hf", DownloadSource.DEFAULT: "llava-hf/llava-1.5-7b-hf",
DownloadSource.MODELSCOPE: "swift/llava-1.5-7b-hf",
}, },
"LLaVA1.5-13B-Chat": { "LLaVA-1.5-13B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-1.5-13b-hf", DownloadSource.DEFAULT: "llava-hf/llava-1.5-13b-hf",
DownloadSource.MODELSCOPE: "swift/llava-1.5-13b-hf",
}, },
}, },
template="llava", template="llava",
@ -835,6 +819,117 @@ register_model_group(
) )
register_model_group(
models={
"LLaVA-NeXT-7B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-v1.6-vicuna-7b-hf",
DownloadSource.MODELSCOPE: "swift/llava-v1.6-vicuna-7b-hf",
},
"LLaVA-NeXT-13B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-v1.6-vicuna-13b-hf",
DownloadSource.MODELSCOPE: "swift/llava-v1.6-vicuna-13b-hf",
},
},
template="llava_next",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-Mistral-7B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-v1.6-mistral-7b-hf",
DownloadSource.MODELSCOPE: "swift/llava-v1.6-mistral-7b-hf",
},
},
template="llava_next_mistral",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-Llama3-8B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llama3-llava-next-8b-hf",
DownloadSource.MODELSCOPE: "swift/llama3-llava-next-8b-hf",
},
},
template="llava_next_llama3",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-34B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-v1.6-34b-hf",
DownloadSource.MODELSCOPE: "LLM-Research/llava-v1.6-34b-hf",
},
},
template="llava_next_yi",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-72B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-next-72b-hf",
DownloadSource.MODELSCOPE: "AI-ModelScope/llava-next-72b-hf",
},
"LLaVA-NeXT-110B-Chat": {
DownloadSource.DEFAULT: "llava-hf/llava-next-110b-hf",
DownloadSource.MODELSCOPE: "AI-ModelScope/llava-next-110b-hf",
},
},
template="llava_next_qwen",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-Video-7B-Chat": {
DownloadSource.DEFAULT: "llava-hf/LLaVA-NeXT-Video-7B-hf",
DownloadSource.MODELSCOPE: "swift/LLaVA-NeXT-Video-7B-hf",
},
"LLaVA-NeXT-Video-7B-DPO-Chat": {
DownloadSource.DEFAULT: "llava-hf/LLaVA-NeXT-Video-7B-DPO-hf",
DownloadSource.MODELSCOPE: "swift/LLaVA-NeXT-Video-7B-DPO-hf",
},
},
template="llava_next_video",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-Video-7B-32k-Chat": {
DownloadSource.DEFAULT: "llava-hf/LLaVA-NeXT-Video-7B-32K-hf",
DownloadSource.MODELSCOPE: "swift/LLaVA-NeXT-Video-7B-32K-hf",
},
},
template="llava_next_video_mistral",
vision=True,
)
register_model_group(
models={
"LLaVA-NeXT-Video-34B-Chat": {
DownloadSource.DEFAULT: "llava-hf/LLaVA-NeXT-Video-34B-hf",
DownloadSource.MODELSCOPE: "swift/LLaVA-NeXT-Video-34B-hf",
},
"LLaVA-NeXT-Video-34B-DPO-Chat": {
DownloadSource.DEFAULT: "llava-hf/LLaVA-NeXT-Video-34B-DPO-hf",
},
},
template="llava_next_video_yi",
vision=True,
)
register_model_group( register_model_group(
models={ models={
"MiniCPM-2B-SFT-Chat": { "MiniCPM-2B-SFT-Chat": {
@ -1028,27 +1123,27 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"Phi3-4B-4k-Instruct": { "Phi-3-4B-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-Instruct": { "Phi-3-4B-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-Instruct": { "Phi-3-7B-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-Instruct": { "Phi-3-7B-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-Instruct": { "Phi-3-14B-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-Instruct": { "Phi-3-14B-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",
}, },
@ -1091,35 +1186,35 @@ register_model_group(
DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat", DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat",
DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat", DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat",
}, },
"Qwen-1.8B-int8-Chat": { "Qwen-1.8B-Chat-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat-Int8", DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat-Int8",
}, },
"Qwen-1.8B-int4-Chat": { "Qwen-1.8B-Chat-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat-Int4", DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat-Int4",
}, },
"Qwen-7B-int8-Chat": { "Qwen-7B-Chat-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat-Int8", DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat-Int8",
}, },
"Qwen-7B-int4-Chat": { "Qwen-7B-Chat-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat-Int4", DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat-Int4",
}, },
"Qwen-14B-int8-Chat": { "Qwen-14B-Chat-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat-Int8", DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat-Int8",
}, },
"Qwen-14B-int4-Chat": { "Qwen-14B-Chat-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat-Int4", DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat-Int4",
}, },
"Qwen-72B-int8-Chat": { "Qwen-72B-Chat-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat-Int8", DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int8",
}, },
"Qwen-72B-int4-Chat": { "Qwen-72B-Chat-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat-Int4", DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int4",
}, },
@ -1202,75 +1297,75 @@ 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",
}, },
"Qwen1.5-0.5B-int8-Chat": { "Qwen1.5-0.5B-Chat-GPTQ-Int8": {
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",
}, },
"Qwen1.5-0.5B-int4-Chat": { "Qwen1.5-0.5B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat-AWQ",
}, },
"Qwen1.5-1.8B-int8-Chat": { "Qwen1.5-1.8B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat-GPTQ-Int8",
}, },
"Qwen1.5-1.8B-int4-Chat": { "Qwen1.5-1.8B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat-AWQ",
}, },
"Qwen1.5-4B-int8-Chat": { "Qwen1.5-4B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat-GPTQ-Int8",
}, },
"Qwen1.5-4B-int4-Chat": { "Qwen1.5-4B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat-AWQ",
}, },
"Qwen1.5-7B-int8-Chat": { "Qwen1.5-7B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat-GPTQ-Int8",
}, },
"Qwen1.5-7B-int4-Chat": { "Qwen1.5-7B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat-AWQ",
}, },
"Qwen1.5-14B-int8-Chat": { "Qwen1.5-14B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat-GPTQ-Int8",
}, },
"Qwen1.5-14B-int4-Chat": { "Qwen1.5-14B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat-AWQ",
}, },
"Qwen1.5-32B-int4-Chat": { "Qwen1.5-32B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-32B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-32B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-32B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-32B-Chat-AWQ",
}, },
"Qwen1.5-72B-int8-Chat": { "Qwen1.5-72B-Chat-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat-GPTQ-Int8",
}, },
"Qwen1.5-72B-int4-Chat": { "Qwen1.5-72B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat-AWQ",
}, },
"Qwen1.5-110B-int4-Chat": { "Qwen1.5-110B-Chat-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen1.5-110B-Chat-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen1.5-110B-Chat-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen1.5-110B-Chat-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen1.5-110B-Chat-AWQ",
}, },
"Qwen1.5-MoE-A2.7B-int4-Chat": { "Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4": {
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": { "CodeQwen1.5-7B": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B", DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B", DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B",
}, },
"Qwen1.5-Code-7B-Chat": { "CodeQwen1.5-7B-Chat": {
DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat", DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat",
DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat", DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat",
}, },
"Qwen1.5-Code-7B-int4-Chat": { "CodeQwen1.5-7B-Chat-AWQ": {
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",
}, },
@ -1591,51 +1686,51 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"Qwen2VL-2B-Instruct": { "Qwen2-VL-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-Instruct": { "Qwen2-VL-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-72B-Instruct": { "Qwen2-VL-72B-Instruct": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct",
}, },
"Qwen2VL-2B-Instruct-GPTQ-Int8": { "Qwen2-VL-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-Instruct-GPTQ-Int4": { "Qwen2-VL-2B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4",
}, },
"Qwen2VL-2B-Instruct-AWQ": { "Qwen2-VL-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-Instruct-GPTQ-Int8": { "Qwen2-VL-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-Instruct-GPTQ-Int4": { "Qwen2-VL-7B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4",
}, },
"Qwen2VL-7B-Instruct-AWQ": { "Qwen2-VL-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": { "Qwen2-VL-72B-Instruct-GPTQ-Int8": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-GPTQ-Int8", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-GPTQ-Int8",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-GPTQ-Int8", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-GPTQ-Int8",
}, },
"Qwen2VL-72B-Instruct-GPTQ-Int4": { "Qwen2-VL-72B-Instruct-GPTQ-Int4": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-GPTQ-Int4", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-GPTQ-Int4",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-GPTQ-Int4", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-GPTQ-Int4",
}, },
"Qwen2VL-72B-Instruct-AWQ": { "Qwen2-VL-72B-Instruct-AWQ": {
DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-AWQ", DownloadSource.DEFAULT: "Qwen/Qwen2-VL-72B-Instruct-AWQ",
DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-AWQ", DownloadSource.MODELSCOPE: "qwen/Qwen2-VL-72B-Instruct-AWQ",
}, },
@ -1712,11 +1807,11 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"Vicuna1.5-7B-Chat": { "Vicuna-v1.5-7B-Chat": {
DownloadSource.DEFAULT: "lmsys/vicuna-7b-v1.5", DownloadSource.DEFAULT: "lmsys/vicuna-7b-v1.5",
DownloadSource.MODELSCOPE: "Xorbits/vicuna-7b-v1.5", DownloadSource.MODELSCOPE: "Xorbits/vicuna-7b-v1.5",
}, },
"Vicuna1.5-13B-Chat": { "Vicuna-v1.5-13B-Chat": {
DownloadSource.DEFAULT: "lmsys/vicuna-13b-v1.5", DownloadSource.DEFAULT: "lmsys/vicuna-13b-v1.5",
DownloadSource.MODELSCOPE: "Xorbits/vicuna-13b-v1.5", DownloadSource.MODELSCOPE: "Xorbits/vicuna-13b-v1.5",
}, },
@ -1725,6 +1820,17 @@ register_model_group(
) )
register_model_group(
models={
"Video-LLaVA-7B-Chat": {
DownloadSource.DEFAULT: "LanguageBind/Video-LLaVA-7B-hf",
},
},
template="video_llava",
vision=True,
)
register_model_group( register_model_group(
models={ models={
"XuanYuan-6B": { "XuanYuan-6B": {
@ -1735,7 +1841,7 @@ register_model_group(
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B",
}, },
"XuanYuan-2-70B": { "XuanYuan2-70B": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B",
}, },
@ -1747,31 +1853,31 @@ register_model_group(
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat",
}, },
"XuanYuan-2-70B-Chat": { "XuanYuan2-70B-Chat": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat",
}, },
"XuanYuan-6B-int8-Chat": { "XuanYuan-6B-Chat-8bit": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat-8bit", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat-8bit",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat-8bit", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat-8bit",
}, },
"XuanYuan-6B-int4-Chat": { "XuanYuan-6B-Chat-4bit": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat-4bit", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat-4bit",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat-4bit", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat-4bit",
}, },
"XuanYuan-70B-int8-Chat": { "XuanYuan-70B-Chat-8bit": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat-8bit", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat-8bit",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat-8bit", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat-8bit",
}, },
"XuanYuan-70B-int4-Chat": { "XuanYuan-70B-Chat-4bit": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat-4bit", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat-4bit",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat-4bit", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat-4bit",
}, },
"XuanYuan-2-70B-int8-Chat": { "XuanYuan2-70B-Chat-8bit": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat-8bit", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat-8bit",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat-8bit", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat-8bit",
}, },
"XuanYuan-2-70B-int4-Chat": { "XuanYuan2-70B-Chat-4bit": {
DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat-4bit", DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat-4bit",
DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat-4bit", DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat-4bit",
}, },
@ -1876,19 +1982,19 @@ register_model_group(
DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat", DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat",
DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat", DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat",
}, },
"Yi-6B-int8-Chat": { "Yi-6B-Chat-8bits": {
DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat-8bits", DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat-8bits",
DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat-8bits", DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat-8bits",
}, },
"Yi-6B-int4-Chat": { "Yi-6B-Chat-4bits": {
DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat-4bits", DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat-4bits",
DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat-4bits", DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat-4bits",
}, },
"Yi-34B-int8-Chat": { "Yi-34B-Chat-8bits": {
DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat-8bits", DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat-8bits",
DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat-8bits", DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat-8bits",
}, },
"Yi-34B-int4-Chat": { "Yi-34B-Chat-4bits": {
DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat-4bits", DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat-4bits",
DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat-4bits", DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat-4bits",
}, },
@ -1939,10 +2045,10 @@ register_model_group(
register_model_group( register_model_group(
models={ models={
"YiVL-6B-Chat": { "Yi-VL-6B-Chat": {
DownloadSource.DEFAULT: "BUAADreamer/Yi-VL-6B-hf", DownloadSource.DEFAULT: "BUAADreamer/Yi-VL-6B-hf",
}, },
"YiVL-34B-Chat": { "Yi-VL-34B-Chat": {
DownloadSource.DEFAULT: "BUAADreamer/Yi-VL-34B-hf", DownloadSource.DEFAULT: "BUAADreamer/Yi-VL-34B-hf",
}, },
}, },

5
src/llamafactory/model/loader.py
View File

@ -25,7 +25,7 @@ from .model_utils.misc import register_autoclass
from .model_utils.mod import convert_pretrained_model_to_mod, load_mod_pretrained_model from .model_utils.mod import convert_pretrained_model_to_mod, load_mod_pretrained_model
from .model_utils.unsloth import load_unsloth_pretrained_model from .model_utils.unsloth import load_unsloth_pretrained_model
from .model_utils.valuehead import load_valuehead_params from .model_utils.valuehead import load_valuehead_params
from .model_utils.visual import get_image_seqlen from .model_utils.visual import get_image_seqlen, get_patch_size, get_vision_feature_select_strategy
from .patcher import patch_config, patch_model, patch_tokenizer, patch_valuehead_model from .patcher import patch_config, patch_model, patch_tokenizer, patch_valuehead_model
@ -100,9 +100,11 @@ def load_tokenizer(model_args: "ModelArguments") -> "TokenizerModule":
setattr(processor, "tokenizer", tokenizer) setattr(processor, "tokenizer", tokenizer)
setattr(processor, "image_seqlen", get_image_seqlen(config)) setattr(processor, "image_seqlen", get_image_seqlen(config))
setattr(processor, "image_resolution", model_args.image_resolution) setattr(processor, "image_resolution", model_args.image_resolution)
setattr(processor, "patch_size", get_patch_size(config))
setattr(processor, "video_resolution", model_args.video_resolution) setattr(processor, "video_resolution", model_args.video_resolution)
setattr(processor, "video_fps", model_args.video_fps) setattr(processor, "video_fps", model_args.video_fps)
setattr(processor, "video_maxlen", model_args.video_maxlen) setattr(processor, "video_maxlen", model_args.video_maxlen)
setattr(processor, "vision_feature_select_strategy", get_vision_feature_select_strategy(config))
except Exception: except Exception:
processor = None processor = None
@ -155,7 +157,6 @@ def load_model(
load_class = AutoModelForVision2Seq load_class = AutoModelForVision2Seq
else: else:
load_class = AutoModelForCausalLM load_class = AutoModelForCausalLM
if model_args.train_from_scratch: if model_args.train_from_scratch:
model = load_class.from_config(config) model = load_class.from_config(config)
else: else:

2
src/llamafactory/model/model_utils/misc.py
View File

@ -34,7 +34,7 @@ def find_all_linear_modules(model: "PreTrainedModel", freeze_vision_tower: bool)
forbidden_modules.add("output_layer") forbidden_modules.add("output_layer")
elif model_type == "internlm2": elif model_type == "internlm2":
forbidden_modules.add("output") forbidden_modules.add("output")
elif model_type in ["llava", "paligemma"]: elif model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "video_llava"]:
forbidden_modules.add("multi_modal_projector") forbidden_modules.add("multi_modal_projector")
elif model_type == "qwen2_vl": elif model_type == "qwen2_vl":
forbidden_modules.add("merger") forbidden_modules.add("merger")

32
src/llamafactory/model/model_utils/visual.py
View File

@ -92,7 +92,7 @@ def autocast_projector_dtype(model: "PreTrainedModel", model_args: "ModelArgumen
if getattr(model, "quantization_method", None): if getattr(model, "quantization_method", None):
model_type = getattr(model.config, "model_type", None) model_type = getattr(model.config, "model_type", None)
if model_type in ["llava", "paligemma"]: if model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "video_llava"]:
mm_projector: "torch.nn.Module" = getattr(model, "multi_modal_projector") mm_projector: "torch.nn.Module" = getattr(model, "multi_modal_projector")
elif model_type == "qwen2_vl": elif model_type == "qwen2_vl":
mm_projector: "torch.nn.Module" = getattr(getattr(model, "visual"), "merger") mm_projector: "torch.nn.Module" = getattr(getattr(model, "visual"), "merger")
@ -108,7 +108,13 @@ def configure_visual_model(config: "PretrainedConfig") -> None:
Patches VLMs before loading them. Patches VLMs before loading them.
""" """
model_type = getattr(config, "model_type", None) model_type = getattr(config, "model_type", None)
if model_type == "llava": # required for ds zero3 and valuehead models if model_type in [
"llava",
"llava_next",
"llava_next_video",
"paligemma",
"video_llava",
]: # required for ds zero3 and valuehead models
setattr(config, "hidden_size", getattr(config.text_config, "hidden_size", None)) setattr(config, "hidden_size", getattr(config.text_config, "hidden_size", None))
if getattr(config, "is_yi_vl_derived_model", None): if getattr(config, "is_yi_vl_derived_model", None):
@ -122,7 +128,7 @@ def get_forbidden_modules(config: "PretrainedConfig", finetuning_args: "Finetuni
""" """
model_type = getattr(config, "model_type", None) model_type = getattr(config, "model_type", None)
forbidden_modules = set() forbidden_modules = set()
if model_type in ["llava", "paligemma"]: if model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "video_llava"]:
if finetuning_args.freeze_vision_tower: if finetuning_args.freeze_vision_tower:
forbidden_modules.add("vision_tower") forbidden_modules.add("vision_tower")
@ -150,12 +156,28 @@ def get_image_seqlen(config: "PretrainedConfig") -> int:
image_seqlen += 1 image_seqlen += 1
elif model_type == "paligemma": elif model_type == "paligemma":
image_seqlen = config.vision_config.num_image_tokens image_seqlen = config.vision_config.num_image_tokens
elif model_type == "qwen2_vl": # variable length else:
image_seqlen = -1 image_seqlen = -1
return image_seqlen return image_seqlen
def get_patch_size(config: "PretrainedConfig") -> int:
r"""
Computes the patch size of the vit.
"""
patch_size = getattr(config.vision_config, "patch_size", -1)
return patch_size
def get_vision_feature_select_strategy(config: "PretrainedConfig") -> int:
r"""
Get the vision_feature_select_strategy.
"""
vision_feature_select_strategy = getattr(config, "vision_feature_select_strategy", "default")
return vision_feature_select_strategy
def patch_target_modules( def patch_target_modules(
config: "PretrainedConfig", finetuning_args: "FinetuningArguments", target_modules: Sequence[str] config: "PretrainedConfig", finetuning_args: "FinetuningArguments", target_modules: Sequence[str]
) -> Union[str, List[str]]: ) -> Union[str, List[str]]:
@ -164,7 +186,7 @@ def patch_target_modules(
""" """
model_type = getattr(config, "model_type", None) model_type = getattr(config, "model_type", None)
if finetuning_args.freeze_vision_tower: if finetuning_args.freeze_vision_tower:
if model_type in ["llava", "paligemma"]: if model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "video_llava"]:
return "^(?!.*vision_tower).*(?:{}).*".format("|".join(target_modules)) return "^(?!.*vision_tower).*(?:{}).*".format("|".join(target_modules))
elif model_type == "qwen2_vl": elif model_type == "qwen2_vl":
return "^(?!.*visual).*(?:{}).*".format("|".join(target_modules)) return "^(?!.*visual).*(?:{}).*".format("|".join(target_modules))

18
src/llamafactory/webui/common.py
View File

@ -115,13 +115,6 @@ def get_model_path(model_name: str) -> str:
return model_path return model_path
def get_prefix(model_name: str) -> str:
r"""
Gets the prefix of the model name to obtain the model family.
"""
return model_name.split("-")[0]
def get_model_info(model_name: str) -> Tuple[str, str]: def get_model_info(model_name: str) -> Tuple[str, str]:
r""" r"""
Gets the necessary information of this model. Gets the necessary information of this model.
@ -137,21 +130,14 @@ 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 ( return DEFAULT_TEMPLATE.get(model_name, "default")
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"
def get_visual(model_name: str) -> bool: def get_visual(model_name: str) -> bool:
r""" r"""
Judges if the model is a vision language model. Judges if the model is a vision language model.
""" """
return get_prefix(model_name) in VISION_MODELS return model_name in VISION_MODELS
def list_checkpoints(model_name: str, finetuning_type: str) -> "gr.Dropdown": def list_checkpoints(model_name: str, finetuning_type: str) -> "gr.Dropdown":

48
tests/data/test_mm_plugin.py
View File

@ -136,6 +136,38 @@ def test_llava_plugin():
_check_plugin(**check_inputs) _check_plugin(**check_inputs)
def test_llava_next_plugin():
tokenizer, processor = _load_tokenizer_module(model_name_or_path="llava-hf/llava-v1.6-vicuna-7b-hf")
llava_next_plugin = get_mm_plugin(name="llava_next", image_token="<image>")
check_inputs = {"plugin": llava_next_plugin, "tokenizer": tokenizer, "processor": processor}
image_seqlen = 1176
check_inputs["expected_mm_messages"] = [
{
key: value.replace("<image>", "<image>" * image_seqlen)
for key, value in message.items()
}
for message in MM_MESSAGES
]
check_inputs["expected_mm_inputs"] = _get_mm_inputs(processor)
_check_plugin(**check_inputs)
def test_llava_next_video_plugin():
tokenizer, processor = _load_tokenizer_module(model_name_or_path="llava-hf/LLaVA-NeXT-Video-7B-hf")
llava_next_video_plugin = get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>")
check_inputs = {"plugin": llava_next_video_plugin, "tokenizer": tokenizer, "processor": processor}
image_seqlen = 1176
check_inputs["expected_mm_messages"] = [
{
key: value.replace("<image>", "<image>" * image_seqlen)
for key, value in message.items()
}
for message in MM_MESSAGES
]
check_inputs["expected_mm_inputs"] = _get_mm_inputs(processor)
_check_plugin(**check_inputs)
@pytest.mark.skipif(not HF_TOKEN, reason="Gated model.") @pytest.mark.skipif(not HF_TOKEN, reason="Gated model.")
def test_paligemma_plugin(): def test_paligemma_plugin():
tokenizer, processor = _load_tokenizer_module(model_name_or_path="google/paligemma-3b-pt-224") tokenizer, processor = _load_tokenizer_module(model_name_or_path="google/paligemma-3b-pt-224")
@ -167,3 +199,19 @@ def test_qwen2_vl_plugin():
] ]
check_inputs["expected_mm_inputs"] = _get_mm_inputs(processor) check_inputs["expected_mm_inputs"] = _get_mm_inputs(processor)
_check_plugin(**check_inputs) _check_plugin(**check_inputs)
def test_video_llava_plugin():
tokenizer, processor = _load_tokenizer_module(model_name_or_path="LanguageBind/Video-LLaVA-7B-hf")
video_llava_plugin = get_mm_plugin(name="video_llava", image_token="<image>", video_token="<video>")
check_inputs = {"plugin": video_llava_plugin, "tokenizer": tokenizer, "processor": processor}
image_seqlen = 256
check_inputs["expected_mm_messages"] = [
{
key: value.replace("<image>", "<image>" * image_seqlen)
for key, value in message.items()
}
for message in MM_MESSAGES
]
check_inputs["expected_mm_inputs"] = _get_mm_inputs(processor)
_check_plugin(**check_inputs)