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--- |
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library_name: peft |
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datasets: |
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- timdettmers/openassistant-guanaco |
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pipeline_tag: conversational |
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base_model: internlm/internlm2-chat-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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[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/InternLM/xtuner) |
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</div> |
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## Model |
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internlm2-chat-7b-qlora-oasst1 is fine-tuned from [InternLM2-Chat-7B](https://huggingface.co/internlm/internlm2-chat-7b) with [openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset 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/internlm2-chat-7b --adapter xtuner/internlm2-chat-7b-qlora-oasst1 --prompt-template internlm2_chat |
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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 internlm2_chat_7b_qlora_oasst1_e3 |
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``` |
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