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  A bilingual instruction-tuned LoRA model of https://huggingface.co/meta-llama/Llama-2-13b-hf
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  - Instruction-following datasets used: alpaca, alpaca-zh, open assistant
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- - Training framework: [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning)
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  Usage:
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  generate_ids = model.generate(**inputs, max_new_tokens=256, streamer=streamer)
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  ```
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- You could also alternatively launch a CLI demo by using the script in [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning)
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  ```bash
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  python src/cli_demo.py --template default --model_name_or_path hiyouga/Llama-2-Chinese-13b-chat
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  ---
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- The model is trained using the web UI of [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning).
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  ![ui](ui.jpg)
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  A bilingual instruction-tuned LoRA model of https://huggingface.co/meta-llama/Llama-2-13b-hf
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  - Instruction-following datasets used: alpaca, alpaca-zh, open assistant
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+ - Training framework: [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
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  Usage:
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  generate_ids = model.generate(**inputs, max_new_tokens=256, streamer=streamer)
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  ```
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+ You could also alternatively launch a CLI demo by using the script in [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
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  ```bash
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  python src/cli_demo.py --template default --model_name_or_path hiyouga/Llama-2-Chinese-13b-chat
 
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  ---
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+ The model is trained using the web UI of [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory).
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  ![ui](ui.jpg)
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