Chinese-LLaMA-Alpaca-2
Chinese LLaMA-2 & Alpaca-2 models with extended context lengths
GraphCanon updated 3d · GitHub synced 3d
Decision brief
Chinese-LLaMA-Alpaca-2 provides Chinese-specific versions of LLaMA-2 and Alpaca-2 with extended context lengths up to 64K tokens.
Good fit when
- When you need advanced models specifically tailored for the Chinese language, offering better performance compared to generic models
- For projects that require handling very long text contexts up to 64K tokens, suitable for extensive document summarization or detailed dialogue analysis
Avoid when
- If your project requires support for languages other than Chinese, as the focus is on refining Chinese text understanding and generation
- In scenarios where shorter context lengths (less than 16K tokens) are sufficient, as the extended models may be overkill in terms of resource usage
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Slowing (120d since push)
- As of 3d
- Provenance
- Not a fork · Personal account
- As of 3d
- Security (OSV)
- 73 low (73 low)
- As of 1mo
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Install
pip install Chinese-LLaMA-Alpaca-2How it fits your stack(4)
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Evidence and technical details
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Overview
This repository contains Chinese versions of the LLaMA-2 and Alpaca-2 large language models, including both base models and instruction fine-tuned variants. Models are equipped to support longer contextual understanding up to 64K tokens.
Capability facts
- Languages
- python
Source: github.language · Aug 17, 2026
Categories
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 17, 2026)
, [text-generation-webui](https://github.com/oobabooga/text-generation-webui), [LangChain](https://github.com/hwchase17/langchain), [privateGPT](https://github.com/imartSource link
Tags
README
Chinese-LLaMA-Alpaca-3项目启动！
🇨🇳中文 | 🌐English | 📖文档/Docs | ❓提问/Issues | 💬讨论/Discussions | ⚔️竞技场/Arena
本项目基于Meta发布的可商用大模型Llama-2开发，是中文LLaMA&Alpaca大模型的第二期项目，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, llama.cpp, text-generation-webui, LangChain, privateGPT, 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 | 多模态中文LLaMA&Alpaca大模型 | 多模态VLE | 中文MiniRBT | 中文LERT | 中英文PERT | 中文MacBERT | 中文ELECTRA | 中文XLNet | 中文BERT | 知识蒸馏工具TextBrewer | 模型裁剪工具TextPruner | 蒸馏裁剪一体化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
[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
[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
[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
For agents
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