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Support GLM-4/GLM-4-0414/GLM-Z1

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.env.local
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......@@ -16,6 +16,8 @@ USE_MODELSCOPE_HUB=
USE_OPENMIND_HUB=
USE_RAY=
RECORD_VRAM=
OPTIM_TORCH=
NPU_JIT_COMPILE=
# torchrun
FORCE_TORCHRUN=
MASTER_ADDR=
......
Makefile
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.PHONY: build commit quality style test
.PHONY: build commit license quality style test
check_dirs := scripts src tests setup.py
build:
pip install build && python -m build
pip3 install build && python3 -m build
commit:
pre-commit install
pre-commit run --all-files
license:
python3 tests/check_license.py $(check_dirs)
quality:
ruff check $(check_dirs)
ruff format --check $(check_dirs)
......
README.md
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......@@ -28,6 +28,7 @@ LLaMA Factory是一个大语言模型训练和推理的框架，支持了魔搭
| [Qwen1.5 (Code/MoE)/Qwen2/Qwen2.5/QwQ](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B | qwen |
| [XVERSE](https://hf-mirror.com/xverse) | 7B/13B | xverse |
| [OLMo](https://hf-mirror.com/allenai) | 1B/7B | olmo |
| [GLM-4/GLM-4-0414/GLM-Z1](https://huggingface.co/THUDM) | 9B/32B | glm4 |
持续更新中...
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README_en.md
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......@@ -5,7 +5,7 @@
[![GitHub contributors](https://img.shields.io/github/contributors/hiyouga/LLaMA-Factory?color=orange)](https://github.com/hiyouga/LLaMA-Factory/graphs/contributors)
[![GitHub workflow](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml/badge.svg)](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml)
[![PyPI](https://img.shields.io/pypi/v/llamafactory)](https://pypi.org/project/llamafactory/)
[![Citation](https://img.shields.io/badge/citation-349-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
[![Citation](https://img.shields.io/badge/citation-392-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
[![GitHub pull request](https://img.shields.io/badge/PRs-welcome-blue)](https://github.com/hiyouga/LLaMA-Factory/pulls)
[![Twitter](https://img.shields.io/twitter/follow/llamafactory_ai)](https://twitter.com/llamafactory_ai)
......@@ -42,6 +42,7 @@ Choose your path:
- **Local machine**: Please refer to [usage](#getting-started)
- **PAI-DSW (free trial)**: [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) | [DeepSeek-R1-Distill Example](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)
- **Amazon SageMaker**: [Blog](https://aws.amazon.com/cn/blogs/china/a-one-stop-code-free-model-fine-tuning-deployment-platform-based-on-sagemaker-and-llama-factory/)
- **Easy Dataset**: [Fine-tune on Synthetic Data](https://buaa-act.feishu.cn/wiki/GVzlwYcRFiR8OLkHbL6cQpYin7g)
> [!NOTE]
> Except for the above links, all other websites are unauthorized third-party websites. Please carefully use them.
......@@ -106,13 +107,15 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
## Changelog
[25/04/14] We supported fine-tuning the **[GLM-Z1](https://huggingface.co/THUDM/GLM-Z1-9B-0414)** and **[Kimi-VL](https://huggingface.co/moonshotai/Kimi-VL-A3B-Instruct)** models.
[25/04/06] We supported fine-tuning the **[Llama 4](https://ai.meta.com/blog/llama-4-multimodal-intelligence/)** model. See [PR #7611](https://github.com/hiyouga/LLaMA-Factory/pull/7611) to get started.
[25/03/31] We supported fine-tuning the **[Qwen2.5 Omni](https://qwenlm.github.io/blog/qwen2.5-omni/)** model. See [PR #7537](https://github.com/hiyouga/LLaMA-Factory/pull/7537) to get started.
[25/03/15] We supported **[SGLang](https://github.com/sgl-project/sglang)** as inference backend. Try `infer_backend: sglang` to accelerate inference.
[25/03/12] We supported fine-tuning the **[Gemma-3](https://huggingface.co/blog/gemma3)** model.
[25/03/12] We supported fine-tuning the **[Gemma 3](https://huggingface.co/blog/gemma3)** model.
[25/02/24] Announcing **[EasyR1](https://github.com/hiyouga/EasyR1)**, an efficient, scalable and multi-modality RL training framework for efficient GRPO training.
......@@ -122,7 +125,7 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
[25/02/05] We supported fine-tuning the **[Qwen2-Audio](Qwen/Qwen2-Audio-7B-Instruct)** and **[MiniCPM-o-2.6](https://huggingface.co/openbmb/MiniCPM-o-2_6)** on audio understanding tasks.
[25/01/31] We supported fine-tuning the **[DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1)** and **[Qwen2.5-VL](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct)** model.
[25/01/31] We supported fine-tuning the **[DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1)** and **[Qwen2.5-VL](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct)** models.
[25/01/15] We supported **[APOLLO](https://arxiv.org/abs/2412.05270)** optimizer. See [examples](examples/README.md) for usage.
......@@ -238,12 +241,13 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon |
| [Gemma/Gemma 2/CodeGemma](https://huggingface.co/google) | 2B/7B/9B/27B | gemma |
| [Gemma 3](https://huggingface.co/google) | 1B/4B/12B/27B | gemma3/gemma (1B) |
| [GLM-4](https://huggingface.co/THUDM) | 9B | glm4 |
| [GLM-4/GLM-4-0414/GLM-Z1](https://huggingface.co/THUDM) | 9B/32B | glm4 |
| [GPT-2](https://huggingface.co/openai-community) | 0.1B/0.4B/0.8B/1.5B | - |
| [Granite 3.0-3.1](https://huggingface.co/ibm-granite) | 1B/2B/3B/8B | granite3 |
| [Index](https://huggingface.co/IndexTeam) | 1.9B | index |
| [Hunyuan](https://huggingface.co/tencent/) | 7B | hunyuan |
| [Index](https://huggingface.co/IndexTeam) | 1.9B | index |
| [InternLM 2-3](https://huggingface.co/internlm) | 7B/8B/20B | intern2 |
| [Kimi-VL](https://huggingface.co/moonshotai) | 16B | kimi_vl |
| [Llama](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - |
| [Llama 2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 |
| [Llama 3-3.3](https://huggingface.co/meta-llama) | 1B/3B/8B/70B | llama3 |
......@@ -264,9 +268,9 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
| [Phi-3-small](https://huggingface.co/microsoft) | 7B | phi_small |
| [Phi-4](https://huggingface.co/microsoft) | 14B | phi4 |
| [Pixtral](https://huggingface.co/mistralai) | 12B | pixtral |
| [Qwen/QwQ (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [Qwen (1-2.5) (Code/Math/MoE/QwQ)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [Qwen2-Audio](https://huggingface.co/Qwen) | 7B | qwen2_audio |
| [Qwen2.5-Omni](https://huggingface.co/Qwen) | 7B | qwen2_omni |
| [Qwen2.5-Omni](https://huggingface.co/Qwen)\*\* | 7B | qwen2_omni |
| [Qwen2-VL/Qwen2.5-VL/QVQ](https://huggingface.co/Qwen) | 2B/3B/7B/32B/72B | qwen2_vl |
| [Skywork o1](https://huggingface.co/Skywork) | 8B | skywork_o1 |
| [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
......@@ -280,6 +284,10 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
> 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.
>
> Remember to use the **SAME** template in training and inference.
>
> \*: You should install the `transformers` from main branch and use `DISABLE_VERSION_CHECK=1` to skip version check.
>
> \*\*: You need to install a specific version of `transformers` to use the corresponding model.
Please refer to [constants.py](src/llamafactory/extras/constants.py) for a full list of models we supported.
......@@ -383,6 +391,7 @@ You also can add a custom chat template to [template.py](src/llamafactory/data/t
- [DPO mixed (en&zh)](https://huggingface.co/datasets/hiyouga/DPO-En-Zh-20k)
- [UltraFeedback (en)](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized)
- [COIG-P (en&zh)](https://huggingface.co/datasets/m-a-p/COIG-P)
- [RLHF-V (en)](https://huggingface.co/datasets/openbmb/RLHF-V-Dataset)
- [VLFeedback (en)](https://huggingface.co/datasets/Zhihui/VLFeedback)
- [Orca DPO Pairs (en)](https://huggingface.co/datasets/Intel/orca_dpo_pairs)
......@@ -552,11 +561,13 @@ pip install .
### Data Preparation
Please refer to [data/README.md](data/README.md) for checking the details about the format of dataset files. You can either use datasets on HuggingFace / ModelScope / Modelers hub or load the dataset in local disk.
Please refer to [data/README.md](data/README.md) for checking the details about the format of dataset files. You can use datasets on HuggingFace / ModelScope / Modelers hub, load the dataset in local disk, or specify a path to s3/gcs cloud storage.
> [!NOTE]
> Please update `data/dataset_info.json` to use your custom dataset.
You can also use **[Easy Dataset](https://github.com/ConardLi/easy-dataset)** to create synthetic data for fine-tuning.
### Quickstart
Use the following 3 commands to run LoRA **fine-tuning**, **inference** and **merging** of the Llama3-8B-Instruct model, respectively.
......@@ -873,7 +884,7 @@ If you have a project that should be incorporated, please contact via email or c
This repository is licensed under the [Apache-2.0 License](LICENSE).
Please follow the model licenses to use the corresponding model weights: [Baichuan 2](https://huggingface.co/baichuan-inc/Baichuan2-7B-Base/blob/main/Community%20License%20for%20Baichuan%202%20Model.pdf) / [BLOOM](https://huggingface.co/spaces/bigscience/license) / [ChatGLM3](https://github.com/THUDM/ChatGLM3/blob/main/MODEL_LICENSE) / [Command R](https://cohere.com/c4ai-cc-by-nc-license) / [DeepSeek](https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/LICENSE-MODEL) / [Falcon](https://huggingface.co/tiiuae/falcon-180B/blob/main/LICENSE.txt) / [Gemma](https://ai.google.dev/gemma/terms) / [GLM-4](https://huggingface.co/THUDM/glm-4-9b/blob/main/LICENSE) / [GPT-2](https://github.com/openai/gpt-2/blob/master/LICENSE) / [Granite](LICENSE) / [Index](https://huggingface.co/IndexTeam/Index-1.9B/blob/main/LICENSE) / [InternLM](https://github.com/InternLM/InternLM#license) / [Llama](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) / [Llama 2 (LLaVA-1.5)](https://ai.meta.com/llama/license/) / [Llama 3](https://llama.meta.com/llama3/license/) / [MiniCPM](https://github.com/OpenBMB/MiniCPM/blob/main/MiniCPM%20Model%20License.md) / [Mistral/Mixtral/Pixtral](LICENSE) / [OLMo](LICENSE) / [Phi-1.5/Phi-2](https://huggingface.co/microsoft/phi-1_5/resolve/main/Research%20License.docx) / [Phi-3/Phi-4](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/blob/main/LICENSE) / [Qwen](https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT) / [Skywork](https://huggingface.co/Skywork/Skywork-13B-base/blob/main/Skywork%20Community%20License.pdf) / [StarCoder 2](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) / [TeleChat2](https://huggingface.co/Tele-AI/telechat-7B/blob/main/TeleChat%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf) / [XVERSE](https://github.com/xverse-ai/XVERSE-13B/blob/main/MODEL_LICENSE.pdf) / [Yi](https://huggingface.co/01-ai/Yi-6B/blob/main/LICENSE) / [Yi-1.5](LICENSE) / [Yuan 2](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/LICENSE-Yuan)
Please follow the model licenses to use the corresponding model weights: [Baichuan 2](https://huggingface.co/baichuan-inc/Baichuan2-7B-Base/blob/main/Community%20License%20for%20Baichuan%202%20Model.pdf) / [BLOOM](https://huggingface.co/spaces/bigscience/license) / [ChatGLM3](https://github.com/THUDM/ChatGLM3/blob/main/MODEL_LICENSE) / [Command R](https://cohere.com/c4ai-cc-by-nc-license) / [DeepSeek](https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/LICENSE-MODEL) / [Falcon](https://huggingface.co/tiiuae/falcon-180B/blob/main/LICENSE.txt) / [Gemma](https://ai.google.dev/gemma/terms) / [GLM-4](https://huggingface.co/THUDM/glm-4-9b/blob/main/LICENSE) / [GPT-2](https://github.com/openai/gpt-2/blob/master/LICENSE) / [Granite](LICENSE) / [Index](https://huggingface.co/IndexTeam/Index-1.9B/blob/main/LICENSE) / [InternLM](https://github.com/InternLM/InternLM#license) / [Llama](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) / [Llama 2](https://ai.meta.com/llama/license/) / [Llama 3](https://llama.meta.com/llama3/license/) / [Llama 4](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) / [MiniCPM](https://github.com/OpenBMB/MiniCPM/blob/main/MiniCPM%20Model%20License.md) / [Mistral/Mixtral/Pixtral](LICENSE) / [OLMo](LICENSE) / [Phi-1.5/Phi-2](https://huggingface.co/microsoft/phi-1_5/resolve/main/Research%20License.docx) / [Phi-3/Phi-4](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/blob/main/LICENSE) / [Qwen](https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT) / [Skywork](https://huggingface.co/Skywork/Skywork-13B-base/blob/main/Skywork%20Community%20License.pdf) / [StarCoder 2](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) / [TeleChat2](https://huggingface.co/Tele-AI/telechat-7B/blob/main/TeleChat%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf) / [XVERSE](https://github.com/xverse-ai/XVERSE-13B/blob/main/MODEL_LICENSE.pdf) / [Yi](https://huggingface.co/01-ai/Yi-6B/blob/main/LICENSE) / [Yi-1.5](LICENSE) / [Yuan 2](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/LICENSE-Yuan)
## Citation
......
README_zh.md
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......@@ -5,7 +5,7 @@
[![GitHub contributors](https://img.shields.io/github/contributors/hiyouga/LLaMA-Factory?color=orange)](https://github.com/hiyouga/LLaMA-Factory/graphs/contributors)
[![GitHub workflow](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml/badge.svg)](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml)
[![PyPI](https://img.shields.io/pypi/v/llamafactory)](https://pypi.org/project/llamafactory/)
[![Citation](https://img.shields.io/badge/citation-349-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
[![Citation](https://img.shields.io/badge/citation-392-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
[![GitHub pull request](https://img.shields.io/badge/PRs-welcome-blue)](https://github.com/hiyouga/LLaMA-Factory/pulls)
[![Twitter](https://img.shields.io/twitter/follow/llamafactory_ai)](https://twitter.com/llamafactory_ai)
......@@ -40,10 +40,12 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
- **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（昇腾 NPU）**：https://ascend.github.io/docs/sources/llamafactory/
- **Colab（免费）**：https://colab.research.google.com/drive/1d5KQtbemerlSDSxZIfAaWXhKr30QypiK?usp=sharing
- **本地机器**：请见[如何使用](#如何使用)
- **PAI-DSW（免费试用）**：[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) | [DeepSeek-R1-Distill 案例](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)
- **Amazon SageMaker**：[博客](https://aws.amazon.com/cn/blogs/china/a-one-stop-code-free-model-fine-tuning-deployment-platform-based-on-sagemaker-and-llama-factory/)
- **Easy Dataset**：[数据蒸馏微调](https://buaa-act.feishu.cn/wiki/KY9xwTGs1iqHrRkjXBwcZP9WnL9)
> [!NOTE]
> 除上述链接以外的其他网站均为未经许可的第三方网站，请小心甄别。
......@@ -108,13 +110,15 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
## 更新日志
[25/04/14] 我们支持了 **[GLM-Z1](https://huggingface.co/THUDM/GLM-Z1-9B-0414)** 和 **[Kimi-VL](https://huggingface.co/moonshotai/Kimi-VL-A3B-Instruct)** 模型的微调。
[25/04/06] 我们支持了 **[Llama 4](https://ai.meta.com/blog/llama-4-multimodal-intelligence/)** 模型的微调。查看 [PR #7611](https://github.com/hiyouga/LLaMA-Factory/pull/7611) 以使用。
[25/03/31] 我们支持了 **[Qwen2.5 Omni](https://qwenlm.github.io/blog/qwen2.5-omni/)** 模型的微调。查看 [PR #7537](https://github.com/hiyouga/LLaMA-Factory/pull/7537) 以使用。
[25/03/15] 我们支持了 **[SGLang](https://github.com/sgl-project/sglang)** 推理后端，请使用 `infer_backend: sglang` 启用。
[25/03/12] 我们支持了 **[Gemma-3](https://huggingface.co/blog/gemma3)** 模型的微调。
[25/03/12] 我们支持了 **[Gemma 3](https://huggingface.co/blog/gemma3)** 模型的微调。
[25/02/24] 我们宣布开源 **[EasyR1](https://github.com/hiyouga/EasyR1)**，一个高效可扩展的多模态强化学习框架，支持高效的 GRPO 训练。
......@@ -240,17 +244,18 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon |
| [Gemma/Gemma 2/CodeGemma](https://huggingface.co/google) | 2B/7B/9B/27B | gemma |
| [Gemma 3](https://huggingface.co/google) | 1B/4B/12B/27B | gemma3/gemma (1B) |
| [GLM-4](https://huggingface.co/THUDM) | 9B | glm4 |
| [GLM-4/GLM-4-0414/GLM-Z1](https://huggingface.co/THUDM) | 9B/32B | glm4 |
| [GPT-2](https://huggingface.co/openai-community) | 0.1B/0.4B/0.8B/1.5B | - |
| [Granite 3.0-3.1](https://huggingface.co/ibm-granite) | 1B/2B/3B/8B | granite3 |
| [Hunyuan](https://huggingface.co/tencent/) | 7B | hunyuan |
| [Index](https://huggingface.co/IndexTeam) | 1.9B | index |
| [InternLM 2-3](https://huggingface.co/internlm) | 7B/8B/20B | intern2 |
| [Kimi-VL](https://huggingface.co/moonshotai) | 16B | kimi_vl |
| [Llama](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - |
| [Llama 2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 |
| [Llama 3-3.3](https://huggingface.co/meta-llama) | 1B/3B/8B/70B | llama3 |
| [Llama 3.2 Vision](https://huggingface.co/meta-llama) | 11B/90B | mllama |
| [Llama 4](https://huggingface.co/meta-llama) | 109B/402B | llama4 |
| [Llama 3.2 Vision](https://huggingface.co/meta-llama) | 11B/90B | mllama |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | llava |
| [LLaVA-NeXT](https://huggingface.co/llava-hf) | 7B/8B/13B/34B/72B/110B | llava_next |
| [LLaVA-NeXT-Video](https://huggingface.co/llava-hf) | 7B/34B | llava_next_video |
......@@ -266,9 +271,9 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
| [Phi-3-small](https://huggingface.co/microsoft) | 7B | phi_small |
| [Phi-4](https://huggingface.co/microsoft) | 14B | phi4 |
| [Pixtral](https://huggingface.co/mistralai) | 12B | pixtral |
| [Qwen/QwQ (1-2.5) (Code/Math/MoE)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [Qwen (1-2.5) (Code/Math/MoE/QwQ)](https://huggingface.co/Qwen) | 0.5B/1.5B/3B/7B/14B/32B/72B/110B | qwen |
| [Qwen2-Audio](https://huggingface.co/Qwen) | 7B | qwen2_audio |
| [Qwen2.5-Omni](https://huggingface.co/Qwen) | 7B | qwen2_omni |
| [Qwen2.5-Omni](https://huggingface.co/Qwen)\*\* | 7B | qwen2_omni |
| [Qwen2-VL/Qwen2.5-VL/QVQ](https://huggingface.co/Qwen) | 2B/3B/7B/32B/72B | qwen2_vl |
| [Skywork o1](https://huggingface.co/Skywork) | 8B | skywork_o1 |
| [StarCoder 2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
......@@ -282,6 +287,10 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
> 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**。
>
> 请务必在训练和推理时采用**完全一致**的模板。
>
> \*：您需要从 main 分支安装 `transformers` 并使用 `DISABLE_VERSION_CHECK=1` 来跳过版本检查。
>
> \*\*：您需要安装特定版本的 `transformers` 以使用该模型。
项目所支持模型的完整列表请参阅 [constants.py](src/llamafactory/extras/constants.py)。
......@@ -385,6 +394,7 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
- [DPO mixed (en&zh)](https://huggingface.co/datasets/hiyouga/DPO-En-Zh-20k)
- [UltraFeedback (en)](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized)
- [COIG-P (en&zh)](https://huggingface.co/datasets/m-a-p/COIG-P)
- [RLHF-V (en)](https://huggingface.co/datasets/openbmb/RLHF-V-Dataset)
- [VLFeedback (en)](https://huggingface.co/datasets/Zhihui/VLFeedback)
- [Orca DPO Pairs (en)](https://huggingface.co/datasets/Intel/orca_dpo_pairs)
......@@ -560,6 +570,8 @@ pip install .
> [!NOTE]
> 使用自定义数据集时，请更新 `data/dataset_info.json` 文件。
您也可以使用 **[Easy Dataset](https://github.com/ConardLi/easy-dataset)** 构建用于微调的合成数据。
### 快速开始
下面三行命令分别对 Llama3-8B-Instruct 模型进行 LoRA **微调**、**推理**和**合并**。
......@@ -876,7 +888,7 @@ swanlab_run_name: test_run # 可选
本仓库的代码依照 [Apache-2.0](LICENSE) 协议开源。
使用模型权重时，请遵循对应的模型协议：[Baichuan 2](https://huggingface.co/baichuan-inc/Baichuan2-7B-Base/blob/main/Community%20License%20for%20Baichuan%202%20Model.pdf) / [BLOOM](https://huggingface.co/spaces/bigscience/license) / [ChatGLM3](https://github.com/THUDM/ChatGLM3/blob/main/MODEL_LICENSE) / [Command R](https://cohere.com/c4ai-cc-by-nc-license) / [DeepSeek](https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/LICENSE-MODEL) / [Falcon](https://huggingface.co/tiiuae/falcon-180B/blob/main/LICENSE.txt) / [Gemma](https://ai.google.dev/gemma/terms) / [GLM-4](https://huggingface.co/THUDM/glm-4-9b/blob/main/LICENSE) / [GPT-2](https://github.com/openai/gpt-2/blob/master/LICENSE) / [Granite](LICENSE) / [Index](https://huggingface.co/IndexTeam/Index-1.9B/blob/main/LICENSE) / [InternLM](https://github.com/InternLM/InternLM#license) / [Llama](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) / [Llama 2 (LLaVA-1.5)](https://ai.meta.com/llama/license/) / [Llama 3](https://llama.meta.com/llama3/license/) / [MiniCPM](https://github.com/OpenBMB/MiniCPM/blob/main/MiniCPM%20Model%20License.md) / [Mistral/Mixtral/Pixtral](LICENSE) / [OLMo](LICENSE) / [Phi-1.5/Phi-2](https://huggingface.co/microsoft/phi-1_5/resolve/main/Research%20License.docx) / [Phi-3/Phi-4](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/blob/main/LICENSE) / [Qwen](https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT) / [Skywork](https://huggingface.co/Skywork/Skywork-13B-base/blob/main/Skywork%20Community%20License.pdf) / [StarCoder 2](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) / [TeleChat2](https://huggingface.co/Tele-AI/telechat-7B/blob/main/TeleChat%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf) / [XVERSE](https://github.com/xverse-ai/XVERSE-13B/blob/main/MODEL_LICENSE.pdf) / [Yi](https://huggingface.co/01-ai/Yi-6B/blob/main/LICENSE) / [Yi-1.5](LICENSE) / [Yuan 2](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/LICENSE-Yuan)
使用模型权重时，请遵循对应的模型协议：[Baichuan 2](https://huggingface.co/baichuan-inc/Baichuan2-7B-Base/blob/main/Community%20License%20for%20Baichuan%202%20Model.pdf) / [BLOOM](https://huggingface.co/spaces/bigscience/license) / [ChatGLM3](https://github.com/THUDM/ChatGLM3/blob/main/MODEL_LICENSE) / [Command R](https://cohere.com/c4ai-cc-by-nc-license) / [DeepSeek](https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/LICENSE-MODEL) / [Falcon](https://huggingface.co/tiiuae/falcon-180B/blob/main/LICENSE.txt) / [Gemma](https://ai.google.dev/gemma/terms) / [GLM-4](https://huggingface.co/THUDM/glm-4-9b/blob/main/LICENSE) / [GPT-2](https://github.com/openai/gpt-2/blob/master/LICENSE) / [Granite](LICENSE) / [Index](https://huggingface.co/IndexTeam/Index-1.9B/blob/main/LICENSE) / [InternLM](https://github.com/InternLM/InternLM#license) / [Llama](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) / [Llama 2](https://ai.meta.com/llama/license/) / [Llama 3](https://llama.meta.com/llama3/license/) / [Llama 4](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) / [MiniCPM](https://github.com/OpenBMB/MiniCPM/blob/main/MiniCPM%20Model%20License.md) / [Mistral/Mixtral/Pixtral](LICENSE) / [OLMo](LICENSE) / [Phi-1.5/Phi-2](https://huggingface.co/microsoft/phi-1_5/resolve/main/Research%20License.docx) / [Phi-3/Phi-4](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/blob/main/LICENSE) / [Qwen](https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT) / [Skywork](https://huggingface.co/Skywork/Skywork-13B-base/blob/main/Skywork%20Community%20License.pdf) / [StarCoder 2](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) / [TeleChat2](https://huggingface.co/Tele-AI/telechat-7B/blob/main/TeleChat%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf) / [XVERSE](https://github.com/xverse-ai/XVERSE-13B/blob/main/MODEL_LICENSE.pdf) / [Yi](https://huggingface.co/01-ai/Yi-6B/blob/main/LICENSE) / [Yi-1.5](LICENSE) / [Yuan 2](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/LICENSE-Yuan)
## 引用
......
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data/README.md
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......@@ -4,9 +4,10 @@ Currently we support datasets in **alpaca** and **sharegpt** format.
```json
"dataset_name": {
"hf_hub_url": "the name of the dataset repository on the Hugging Face hub. (if specified, ignore script_url and file_name)",
"ms_hub_url": "the name of the dataset repository on the Model Scope hub. (if specified, ignore script_url and file_name)",
"script_url": "the name of the directory containing a dataset loading script. (if specified, ignore file_name)",
"hf_hub_url": "the name of the dataset repository on the Hugging Face hub. (if specified, ignore script_url, file_name and cloud_file_name)",
"ms_hub_url": "the name of the dataset repository on the Model Scope hub. (if specified, ignore script_url, file_name and cloud_file_name)",
"script_url": "the name of the directory containing a dataset loading script. (if specified, ignore file_name and cloud_file_name)",
"cloud_file_name": "the name of the dataset file in s3/gcs cloud storage. (if specified, ignore file_name)",
"file_name": "the name of the dataset folder or dataset file in this directory. (required if above are not specified)",
"formatting": "the format of the dataset. (optional, default: alpaca, can be chosen from {alpaca, sharegpt})",
"ranking": "whether the dataset is a preference dataset or not. (default: False)",
......@@ -85,7 +86,7 @@ Regarding the above dataset, the *dataset description* in `dataset_info.json` sh
### Pre-training Dataset
- [Example dataset](c4_demo.json)
- [Example dataset](c4_demo.jsonl)
In pre-training, only the `text` column will be used for model learning.
......
data/README_zh.md
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......@@ -85,7 +85,7 @@
### 预训练数据集
- [样例数据集](c4_demo.json)
- [样例数据集](c4_demo.jsonl)
在预训练时，只有 `text` 列中的内容会用于模型学习。
......
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data/dataset_info.json
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......@@ -66,6 +66,21 @@
"assistant_tag": "assistant"
}
},
"mllm_video_audio_demo": {
"file_name": "mllm_video_audio_demo.json",
"formatting": "sharegpt",
"columns": {
"messages": "messages",
"videos": "videos",
"audios": "audios"
},
"tags": {
"role_tag": "role",
"content_tag": "content",
"user_tag": "user",
"assistant_tag": "assistant"
}
},
"alpaca_en": {
"hf_hub_url": "llamafactory/alpaca_en",
"ms_hub_url": "llamafactory/alpaca_en",
......@@ -512,6 +527,16 @@
"rejected": "rejected"
}
},
"coig_p": {
"hf_hub_url": "m-a-p/COIG-P",
"ranking": true,
"formatting": "sharegpt",
"columns": {
"messages": "conversations",
"chosen": "chosen",
"rejected": "rejected"
}
},
"rlhf_v": {
"hf_hub_url": "llamafactory/RLHF-V",
"ranking": true,
......@@ -607,7 +632,7 @@
}
},
"c4_demo": {
"file_name": "c4_demo.json",
"file_name": "c4_demo.jsonl",
"columns": {
"prompt": "text"
}
......
data/mllm_video_audio_demo.json 0 → 100644
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[
{
"messages": [
{
"content": "<video><audio>What is the video describing?",
"role": "user"
},
{
"content": "A girl who is drawing a picture of a guitar and feel nervous.",
"role": "assistant"
}
],
"videos": [
"mllm_demo_data/4.mp4"
],
"audios": [
"mllm_demo_data/4.mp3"
]
},
{
"messages": [
{
"content": "<video><audio>What does this girl say?",
"role": "user"
},
{
"content": "She says: 'Hello! Take a look at what am I drawing!'",
"role": "assistant"
}
],
"videos": [
"mllm_demo_data/4.mp4"
],
"audios": [
"mllm_demo_data/4.mp3"
]
},
{
"messages": [
{
"content": "<video><audio>What is this girl drawing with?",
"role": "user"
},
{
"content": "She is drawing with an iPad.",
"role": "assistant"
}
],
"videos": [
"mllm_demo_data/4.mp4"
],
"audios": [
"mllm_demo_data/4.mp3"
]
}
]
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FROM image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.4.1-ubuntu22.04-dtk25.04-py3.10
\ No newline at end of file
docker/docker-cuda/Dockerfile 0 → 100644
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# Default use the NVIDIA official image with PyTorch 2.6.0
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/index.html
ARG BASE_IMAGE=nvcr.io/nvidia/pytorch:24.12-py3
FROM ${BASE_IMAGE}
# Define environments
ENV MAX_JOBS=4
ENV FLASH_ATTENTION_FORCE_BUILD=TRUE
ENV VLLM_WORKER_MULTIPROC_METHOD=spawn
# Define installation arguments
ARG INSTALL_BNB=false
ARG INSTALL_VLLM=false
ARG INSTALL_DEEPSPEED=false
ARG INSTALL_FLASHATTN=false
ARG INSTALL_LIGER_KERNEL=false
ARG INSTALL_HQQ=false
ARG INSTALL_EETQ=false
ARG PIP_INDEX=https://pypi.org/simple
ARG HTTP_PROXY=
# Set the working directory
WORKDIR /app
# Set http proxy
RUN if [ -n "$HTTP_PROXY" ]; then \
echo "Configuring proxy..."; \
export http_proxy=$HTTP_PROXY; \
export https_proxy=$HTTP_PROXY; \
fi
# Install the requirements
COPY requirements.txt /app
RUN pip config set global.index-url "$PIP_INDEX" && \
pip config set global.extra-index-url "$PIP_INDEX" && \
python -m pip install --upgrade pip && \
if [ -n "$HTTP_PROXY" ]; then \
python -m pip install --proxy=$HTTP_PROXY -r requirements.txt; \
else \
python -m pip install -r requirements.txt; \
fi
# Copy the rest of the application into the image
COPY . /app
# Install the LLaMA Factory
RUN EXTRA_PACKAGES="metrics"; \
if [ "$INSTALL_BNB" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},bitsandbytes"; \
fi; \
if [ "$INSTALL_VLLM" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},vllm"; \
fi; \
if [ "$INSTALL_DEEPSPEED" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
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; \
if [ -n "$HTTP_PROXY" ]; then \
pip install --proxy=$HTTP_PROXY -e ".[$EXTRA_PACKAGES]"; \
else \
pip install -e ".[$EXTRA_PACKAGES]"; \
fi
# Rebuild flash attention
RUN pip uninstall -y transformer-engine flash-attn && \
if [ "$INSTALL_FLASHATTN" == "true" ]; then \
pip uninstall -y ninja && \
if [ -n "$HTTP_PROXY" ]; then \
pip install --proxy=$HTTP_PROXY ninja && \
pip install --proxy=$HTTP_PROXY --no-cache-dir flash-attn --no-build-isolation; \
else \
pip install ninja && \
pip install --no-cache-dir flash-attn --no-build-isolation; \
fi; \
fi
# Unset http proxy
RUN if [ -n "$HTTP_PROXY" ]; then \
unset http_proxy; \
unset https_proxy; \
fi
# Set up volumes
VOLUME [ "/root/.cache/huggingface", "/root/.cache/modelscope", "/app/data", "/app/output" ]
# Expose port 7860 for the LLaMA Board
ENV GRADIO_SERVER_PORT 7860
EXPOSE 7860
# Expose port 8000 for the API service
ENV API_PORT 8000
EXPOSE 8000
docker/docker-cuda/docker-compose.yml 0 → 100644
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services:
llamafactory:
build:
dockerfile: ./docker/docker-cuda/Dockerfile
context: ../..
args:
INSTALL_BNB: "false"
INSTALL_VLLM: "false"
INSTALL_DEEPSPEED: "false"
INSTALL_FLASHATTN: "false"
INSTALL_LIGER_KERNEL: "false"
INSTALL_HQQ: "false"
INSTALL_EETQ: "false"
PIP_INDEX: https://pypi.org/simple
container_name: llamafactory
volumes:
- ../../hf_cache:/root/.cache/huggingface
- ../../ms_cache:/root/.cache/modelscope
- ../../om_cache:/root/.cache/openmind
- ../../data:/app/data
- ../../output:/app/output
ports:
- "7860:7860"
- "8000:8000"
ipc: host
tty: true
shm_size: "16gb"
stdin_open: true
command: bash
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: "all"
capabilities: [gpu]
restart: unless-stopped
docker/docker-npu/Dockerfile 0 → 100644
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# Use the Ubuntu 22.04 image with CANN 8.0.rc1
# More versions can be found at https://hub.docker.com/r/ascendai/cann/tags
# FROM ascendai/cann:8.0.rc1-910-ubuntu22.04-py3.8
FROM ascendai/cann:8.0.0-910b-ubuntu22.04-py3.10
# FROM ascendai/cann:8.0.rc1-910-openeuler22.03-py3.8
# FROM ascendai/cann:8.0.rc1-910b-openeuler22.03-py3.8
# Define environments
ENV DEBIAN_FRONTEND=noninteractive
# Define installation arguments
ARG INSTALL_DEEPSPEED=false
ARG PIP_INDEX=https://pypi.org/simple
ARG TORCH_INDEX=https://download.pytorch.org/whl/cpu
ARG HTTP_PROXY=
# Set the working directory
WORKDIR /app
# Set http proxy
RUN if [ -n "$HTTP_PROXY" ]; then \
echo "Configuring proxy..."; \
export http_proxy=$HTTP_PROXY; \
export https_proxy=$HTTP_PROXY; \
fi
# Install the requirements
COPY requirements.txt /app
RUN pip config set global.index-url "$PIP_INDEX" && \
pip config set global.extra-index-url "$TORCH_INDEX" && \
python -m pip install --upgrade pip && \
if [ -n "$HTTP_PROXY" ]; then \
python -m pip install --proxy=$HTTP_PROXY -r requirements.txt; \
else \
python -m pip install -r requirements.txt; \
fi
# Copy the rest of the application into the image
COPY . /app
# Install the LLaMA Factory
RUN EXTRA_PACKAGES="torch-npu,metrics"; \
if [ "$INSTALL_DEEPSPEED" == "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
fi; \
if [ -n "$HTTP_PROXY" ]; then \
pip install --proxy=$HTTP_PROXY -e ".[$EXTRA_PACKAGES]"; \
else \
pip install -e ".[$EXTRA_PACKAGES]"; \
fi
# Unset http proxy
RUN if [ -n "$HTTP_PROXY" ]; then \
unset http_proxy; \
unset https_proxy; \
fi
# Set up volumes
VOLUME [ "/root/.cache/huggingface", "/root/.cache/modelscope", "/app/data", "/app/output" ]
# Expose port 7860 for the LLaMA Board
ENV GRADIO_SERVER_PORT 7860
EXPOSE 7860
# Expose port 8000 for the API service
ENV API_PORT 8000
EXPOSE 8000
docker/docker-npu/docker-compose.yml 0 → 100644
View file @ 581d366d
services:
llamafactory:
build:
dockerfile: ./docker/docker-npu/Dockerfile
context: ../..
args:
INSTALL_DEEPSPEED: "false"
PIP_INDEX: https://pypi.org/simple
container_name: llamafactory
volumes:
- ../../hf_cache:/root/.cache/huggingface
- ../../ms_cache:/root/.cache/modelscope
- ../../om_cache:/root/.cache/openmind
- ../../data:/app/data
- ../../output:/app/output
- /usr/local/dcmi:/usr/local/dcmi
- /usr/local/bin/npu-smi:/usr/local/bin/npu-smi
- /usr/local/Ascend/driver:/usr/local/Ascend/driver
- /etc/ascend_install.info:/etc/ascend_install.info
ports:
- "7860:7860"
- "8000:8000"
ipc: host
tty: true
shm_size: "16gb"
stdin_open: true
command: bash
devices:
- /dev/davinci0
- /dev/davinci_manager
- /dev/devmm_svm
- /dev/hisi_hdc
restart: unless-stopped
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