GraphCanon updated 2w · GitHub synced 2w
Decision brief
Luotuo-Chinese-LLM is an open-source project for Chinese language models with a focus on large-scale models, embeddings, and applications like conversational QA.
Good fit when
- When you need specialized Chinese language modeling capabilities
- For tasks requiring cultural nuance specific to Chinese context
Avoid when
- If your project requires heavy Western or non-Chinese linguistic support
- In scenarios needing real-time large-scale deployment without proper tuning
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (1063d since push)
- As of 2w
- Provenance
- Not a fork · Personal account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/LC1332/Luotuo-Chinese-LLMSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
骆驼(Luotuo)项目是由冷子昂 @ 商汤科技, 陈启源 @ 华中师范大学及李鲁鲁 @ 商汤科技 发起的中国语言模型开源项目,涵盖一系列大型语模、数据、管线和应用。
Capability facts
- Languages
- jupyter notebook
Source: github.language · Aug 1, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 1, 2026)
骆驼嵌入: Generative Text Embedding Model distilled from OpenAI APISource link
Tags
README
English | 中文 | 快速上手 | 赞助 | 赞助 | 人员和贡献 | 相关项目 | 骆驼读论文
骆驼(Luotuo): 开源中文大语言模型
骆驼(Luotuo)项目是由冷子昂 @ 商汤科技, 陈启源 @ 华中师范大学 以及 李鲁鲁 @ 商汤科技 发起的中文大语言模型开源项目,包含了一系列大语言模型、数据、管线和应用。
骆驼项目不是商汤科技的官方产品。
我们将项目命名为 骆驼 Luotuo (Camel) 主要是因为,Meta之前的项目LLaMA(驼马)和斯坦福之前的项目alpaca(羊驼)都属于偶蹄目-骆驼科(Artiodactyla-Camelidae)。而且骆驼科只有三个属,再不起这名字就来不及了。
项目重要更新 [ ... ]
[2023-07-12] 骆驼嵌入更新中模型 。我们后面将准备再训一个英语的嵌入模型。
[2023-06-07] 最近很多精力都在做 Chat凉宫春日, 可以点这个体验 ,这个项目还在持续招人, 欢迎联系
子项目一览
For agents
This page has a .md twin and JSON over the API.