---
title: "Chinese-LLaMA-Alpaca-2"
type: "tool"
slug: "ymcui-chinese-llama-alpaca-2"
canonical_url: "https://www.graphcanon.com/tools/ymcui-chinese-llama-alpaca-2"
github_url: "https://github.com/ymcui/Chinese-LLaMA-Alpaca-2"
homepage_url: null
stars: 7134
forks: 564
primary_language: "Python"
license: "Apache-2.0"
categories: ["llm-frameworks", "developer-tools"]
tags: ["64k", "nlp", "rlhf", "llama-2", "alpaca-2", "flash-attention"]
updated_at: "2026-07-07T18:37:14.416806+00:00"
---
# Chinese-LLaMA-Alpaca-2
> 中文LLaMA-2 & Alpaca-2 LLMs with 64K long context models
This repository contains Chinese versions of the LLaMA and Alpaca language models, optimized for large-scale text data, supporting up to 64k context length, and including variations like RLHF fine-tuned models.
## Facts
- Repository: https://github.com/ymcui/Chinese-LLaMA-Alpaca-2
- Stars: 7,134 · Forks: 564 · Open issues: 6 · Watchers: 74
- Primary language: Python
- License: Apache-2.0
- Last pushed: 2026-04-19T00:58:50+00:00
## Categories
- [LLM Frameworks](/categories/llm-frameworks.md)
- [Developer Tools](/categories/developer-tools.md)
## Tags
64k, nlp, rlhf, llama-2, alpaca-2, flash-attention
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## README (excerpt)
```text
# [Chinese-LLaMA-Alpaca-3](https://github.com/ymcui/Chinese-LLaMA-Alpaca-3)项目启动！
[**🇨🇳中文**](./README.md) | [**🌐English**](./README_EN.md) | [**📖文档/Docs**](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/wiki) | [**❓提问/Issues**](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/issues) | [**💬讨论/Discussions**](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/discussions) | [**⚔️竞技场/Arena**](http://llm-arena.ymcui.com/)
本项目基于Meta发布的可商用大模型[Llama-2](https://github.com/facebookresearch/llama)开发，是[中文LLaMA&Alpaca大模型](https://github.com/ymcui/Chinese-LLaMA-Alpaca)的第二期项目，开源了**中文LLaMA-2基座模型和Alpaca-2指令精调大模型**。这些模型**在原版Llama-2的基础上扩充并优化了中文词表**，使用了大规模中文数据进行增量预训练，进一步提升了中文基础语义和指令理解能力，相比一代相关模型获得了显著性能提升。相关模型**支持FlashAttention-2训练**。标准版模型支持4K上下文长度，**长上下文版模型支持16K、64k上下文长度**。**RLHF系列模型**为标准版模型基础上进行人类偏好对齐精调，相比标准版模型在**正确价值观体现**方面获得了显著性能提升。
#### 本项目主要内容
- 🚀 针对Llama-2模型扩充了**新版中文词表**，开源了中文LLaMA-2和Alpaca-2大模型
- 🚀 开源了预训练脚本、指令精调脚本，用户可根据需要进一步训练模型
- 🚀 使用个人电脑的CPU/GPU快速在本地进行大模型量化和部署体验
- 🚀 支持[🤗transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp), [text-generation-webui](https://github.com/oobabooga/text-generation-webui), [LangChain](https://github.com/hwchase17/langchain), [privateGPT](https://github.com/imartinez/privateGPT), [vLLM](https://github.com/vllm-project/vllm)等LLaMA生态
#### 已开源的模型
- 基座模型（4K上下文）：Chinese-LLaMA-2 (1.3B, 7B, 13B)
- 聊天模型（4K上下文）：Chinese-Alpaca-2 (1.3B, 7B, 13B)
- 长上下文模型（16K/64K）：
- Chinese-LLaMA-2-16K (7B, 13B) 、Chinese-Alpaca-2-16K (7B, 13B)
- Chinese-LLaMA-2-64K (7B)、Chinese-Alpaca-2-64K (7B)
- 偏好对齐模型：Chinese-Alpaca-2-RLHF (1.3B, 7B)
----
[中文LLaMA&Alpaca大模型](https://github.com/ymcui/Chinese-LLaMA-Alpaca) | [多模态中文LLaMA&Alpaca大模型](https://github.com/airaria/Visual-Chinese-LLaMA-Alpaca) | [多模态VLE](https://github.com/iflytek/VLE) | [中文MiniRBT](https://github.com/iflytek/MiniRBT) | [中文LERT](https://github.com/ymcui/LERT) | [中英文PERT](https://github.com/ymcui/PERT) | [中文MacBERT](https://github.com/ymcui/MacBERT) | [中文ELECTRA](https://github.com/ymcui/Chinese-ELECTRA) | [中文XLNet](https://github.com/ymcui/Chinese-XLNet) | [中文BERT](https://github.com/ymcui/Chinese-BERT-wwm) | [知识蒸馏工具TextBrewer](https://github.com/airaria/TextBrewer) | [模型裁剪工具TextPruner](https://github.com/airaria/TextPruner) | [蒸馏裁剪一体化GRAIN](https://github.com/airaria/GRAIN)
## 新闻
**[2024/04/30] Chinese-LLaMA-Alpaca-3 已正式发布，开源基于Llama-3的Llama-3-Chinese-8B和Llama-3-Chinese-8B-Instruct，推荐所有一期、二期项目用户升级至三代模型，请参阅：https://github.com/ymcui/Chinese-LLaMA-Alpaca-3**
[2024/03/27] 本项目已入驻机器之心SOTA!模型平台，欢迎关注：https://sota.jiqizhixin.com/project/chinese-llama-alpaca-2
[2024/01/23] 添加新版GGUF模型（imatrix量化）、AWQ量化模型，支持vLLM下加载YaRN长上下文模型。详情查看[📚 v4.1版本发布日志](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/releases/tag/v4.1)
[2023/12/29] 发布长上下文模型Chinese-LLaMA-2-7B-64K和Chinese-Alpaca-2-7B-64K，同时发布经过人类偏好对齐（RLHF）的Chinese-Alpaca-2-RLHF（1.3B/7B）。详情查看[📚 v4.0版本发布日志](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/releases/tag/v4.0)
[2023/09/01] 发布长上下文模型Chinese-Alpaca-2-7B-16K和Chinese-Alpaca-2-13B-16K，该模型可直接应用于下游任务，例如privateGPT等。详情查看[📚 v3.1版本发布日志](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/releases/tag/v3.1)
[2023/08/25] 发布长上下文模型Chinese-LLaMA-2-7B-16K和Chinese-LLaMA-2-13B-16K，支持16K上下文，并可通过NTK方法进一步扩展至24K+。详情查看
```
---
**Machine-readable endpoints**
- JSON: [`/api/graphcanon/tools/ymcui-chinese-llama-alpaca-2`](/api/graphcanon/tools/ymcui-chinese-llama-alpaca-2)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)
_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_