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README.md
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**Related models👇**
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* Long context base models
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* [Chinese-LLaMA-2-7B-16K (full model)](https://huggingface.co/
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* [Chinese-LLaMA-2-LoRA-7B-16K (LoRA model)](https://huggingface.co/
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* [Chinese-LLaMA-2-13B-16K (full model)](https://huggingface.co/
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* [Chinese-LLaMA-2-LoRA-13B-16K (LoRA model)](https://huggingface.co/
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* Base models
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* [Chinese-LLaMA-2-7B (full model)](https://huggingface.co/
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* [Chinese-LLaMA-2-LoRA-7B (LoRA model)](https://huggingface.co/
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* [Chinese-LLaMA-2-13B (full model)](https://huggingface.co/
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* [Chinese-LLaMA-2-LoRA-13B (LoRA model)](https://huggingface.co/
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* Instruction/Chat models
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* [Chinese-Alpaca-2-7B (full model)](https://huggingface.co/
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* [Chinese-Alpaca-2-LoRA-7B (LoRA model)](https://huggingface.co/
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* [Chinese-Alpaca-2-13B (full model)](https://huggingface.co/
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* [Chinese-Alpaca-2-LoRA-13B (LoRA model)](https://huggingface.co/
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# Description of Chinese-LLaMA-Alpaca-2
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This project is based on the Llama-2, released by Meta, and it is the second generation of the Chinese LLaMA & Alpaca LLM project. We open-source Chinese LLaMA-2 (foundation model) and Alpaca-2 (instruction-following model). These models have been expanded and optimized with Chinese vocabulary beyond the original Llama-2. We used large-scale Chinese data for incremental pre-training, which further improved the fundamental semantic understanding of the Chinese language, resulting in a significant performance improvement compared to the first-generation models. The relevant models support a 4K context and can be expanded up to 18K+ using the NTK method.
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**Related models👇**
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* Long context base models
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+
* [Chinese-LLaMA-2-7B-16K (full model)](https://huggingface.co/hfl/chinese-llama-2-7b-16k)
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* [Chinese-LLaMA-2-LoRA-7B-16K (LoRA model)](https://huggingface.co/hfl/chinese-llama-2-lora-7b-16k)
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* [Chinese-LLaMA-2-13B-16K (full model)](https://huggingface.co/hfl/chinese-llama-2-13b-16k)
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* [Chinese-LLaMA-2-LoRA-13B-16K (LoRA model)](https://huggingface.co/hfl/chinese-llama-2-lora-13b-16k)
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* Base models
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+
* [Chinese-LLaMA-2-7B (full model)](https://huggingface.co/hfl/chinese-llama-2-7b)
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+
* [Chinese-LLaMA-2-LoRA-7B (LoRA model)](https://huggingface.co/hfl/chinese-llama-2-lora-7b)
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+
* [Chinese-LLaMA-2-13B (full model)](https://huggingface.co/hfl/chinese-llama-2-13b)
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* [Chinese-LLaMA-2-LoRA-13B (LoRA model)](https://huggingface.co/hfl/chinese-llama-2-lora-13b)
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* Instruction/Chat models
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* [Chinese-Alpaca-2-7B (full model)](https://huggingface.co/hfl/chinese-alpaca-2-7b)
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+
* [Chinese-Alpaca-2-LoRA-7B (LoRA model)](https://huggingface.co/hfl/chinese-alpaca-2-lora-7b)
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* [Chinese-Alpaca-2-13B (full model)](https://huggingface.co/hfl/chinese-alpaca-2-13b)
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* [Chinese-Alpaca-2-LoRA-13B (LoRA model)](https://huggingface.co/hfl/chinese-alpaca-2-lora-13b)
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# Description of Chinese-LLaMA-Alpaca-2
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This project is based on the Llama-2, released by Meta, and it is the second generation of the Chinese LLaMA & Alpaca LLM project. We open-source Chinese LLaMA-2 (foundation model) and Alpaca-2 (instruction-following model). These models have been expanded and optimized with Chinese vocabulary beyond the original Llama-2. We used large-scale Chinese data for incremental pre-training, which further improved the fundamental semantic understanding of the Chinese language, resulting in a significant performance improvement compared to the first-generation models. The relevant models support a 4K context and can be expanded up to 18K+ using the NTK method.
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