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--- |
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library_name: peft |
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datasets: |
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- tatsu-lab/alpaca |
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- silk-road/alpaca-data-gpt4-chinese |
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pipeline_tag: conversational |
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base_model: internlm/internlm-7b |
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--- |
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<div align="center"> |
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<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/> |
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[](https://github.com/InternLM/xtuner) |
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</div> |
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## Model |
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internlm-7b-qlora-alpaca-enzh is fine-tuned from [InternLM-7B](https://huggingface.co./internlm/internlm-7b) with [alpaca en](https://huggingface.co./datasets/tatsu-lab/alpaca) / [zh](https://huggingface.co./datasets/silk-road/alpaca-data-gpt4-chinese) datasets by [XTuner](https://github.com/InternLM/xtuner). |
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## Quickstart |
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### Usage with XTuner CLI |
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#### Installation |
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```shell |
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pip install xtuner |
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``` |
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#### Chat |
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```shell |
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xtuner chat internlm/internlm-7b --adapter xtuner/internlm-7b-qlora-alpaca-enzh --prompt-template internlm_chat --system-template alpaca |
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``` |
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#### Fine-tune |
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Use the following command to quickly reproduce the fine-tuning results. |
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```shell |
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xtuner train internlm_7b_qlora_alpaca_enzh_e3 |
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``` |
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