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79 lines
3.4 KiB
Markdown
79 lines
3.4 KiB
Markdown
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<h1 align="center">LLM SFT Example</h1>
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<p align="center">
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<img src="https://img.shields.io/badge/python-%E2%89%A53.8-5be.svg">
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<img src="https://img.shields.io/badge/pytorch-%E2%89%A51.12%20%7C%20%E2%89%A52.0-orange.svg">
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<a href="https://github.com/modelscope/modelscope/"><img src="https://img.shields.io/badge/modelscope-%E2%89%A51.8.1-5D91D4.svg"></a>
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<a href="https://github.com/modelscope/swift/"><img src="https://img.shields.io/badge/ms--swift-%E2%89%A51.0.0-6FEBB9.svg"></a>
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</p>
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<p align="center">
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<a href="https://modelscope.cn/home">Modelscope Hub</a>
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<br>
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<a href="README_CN.md">中文</a>  ｜  English
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</p>
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## Note!!!
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1. This README.md file is copied from [ms-swift README.md](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/README.md)
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2. This directory has been migrated to [ms-swift](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm), and the files in this directory are no longer maintained.
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## Features
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1. supported sft method: lora, qlora, full, ...
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2. supported models: [**qwen-7b**](https://github.com/QwenLM/Qwen-7B), baichuan-7b, baichuan-13b, chatglm2-6b, llama2-7b, llama2-13b, llama2-70b, openbuddy-llama2-13b, ...
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3. supported feature: quantization, ddp, model parallelism(device map), gradient checkpoint, gradient accumulation steps, push to modelscope hub, custom datasets, notebook compatibility, tensorboard, warmup, lr scheduler, resume from ckpt, ...
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4. supported datasets: alpaca-en(gpt4), alpaca-zh(gpt4), finance-en, multi-alpaca-all, multi-alpaca-ar, multi-alpaca-de, multi-alpaca-es, multi-alpaca-fr, multi-alpaca-id, multi-alpaca-ja, multi-alpaca-ko, multi-alpaca-pt, multi-alpaca-ru, multi-alpaca-th, multi-alpaca-vi, code-en, instinwild-en, instinwild-zh, ...
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## Prepare the Environment
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```bash
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# Please note the cuda version
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conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia -y
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pip install sentencepiece charset_normalizer cpm_kernels tiktoken -U
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pip install matplotlib tqdm tensorboard -U
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pip install transformers datasets -U
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pip install accelerate transformers_stream_generator -U
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# Recommended installation from source code for faster bug fixes
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git clone https://github.com/modelscope/swift.git
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cd swift
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pip install -r requirements.txt
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pip install .
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# same as modelscope...(git clone ...)
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# You can also install it from pypi
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pip install ms-swift modelscope -U
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```
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## Run SFT and Inference
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```bash
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git clone https://github.com/modelscope/swift.git
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cd swift/examples/pytorch/llm
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# sft(qlora) and infer qwen-7b, Requires 10GB VRAM.
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bash scripts/qwen_7b/qlora/sft.sh
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bash scripts/qwen_7b/qlora/infer.sh
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# sft(qlora+ddp) and infer qwen-7b, Requires 4*10GB VRAM.
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bash scripts/qwen_7b/qlora_ddp/sft.sh
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bash scripts/qwen_7b/qlora_ddp/infer.sh
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# sft(full) and infer qwen-7b, Requires 95GB VRAM.
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bash scripts/qwen_7b/full/sft.sh
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bash scripts/qwen_7b/full/infer.sh
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# For more scripts, please see `scripts/` folder
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```
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## Extend Datasets
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1. If you need to extend the model, you can modify the `MODEL_MAPPING` in `utils/models.py`. `model_id` can be specified as a local path. In this case, `revision` doesn't work.
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2. If you need to extend or customize the dataset, you can modify the `DATASET_MAPPING` in `utils/datasets.py`. You need to customize the `get_*_dataset` function, which returns a dataset with two columns: `instruction`, `output`.
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## TODO
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1. Support multi-round
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2. RLHF
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3. more models: Qwen-7B-Chat (use same prompt)
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4. more datasets
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5. metrics
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6. ...
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