--- title: "Baichuan-7B" type: "tool" slug: "baichuan-inc-baichuan-7b" canonical_url: "https://www.graphcanon.com/tools/baichuan-inc-baichuan-7b" github_url: "https://github.com/baichuan-inc/Baichuan-7B" homepage_url: "https://huggingface.co/baichuan-inc/baichuan-7B" stars: 5652 forks: 501 primary_language: "Python" license: "Apache-2.0" categories: ["llm-frameworks"] tags: ["llama", "chinese", "artificial-intelligence", "large-language-models", "gpt-4", "chatgpt", "huggingface", "ceval"] updated_at: "2026-07-07T18:39:22.456848+00:00" --- # Baichuan-7B > A large-scale pretraining language model for natural language processing tasks. Baichuan-7B is a 7 billion parameter, open-source language model developed by BaiChuan-Inc. Trained on approximately 1.2 trillion tokens, it supports both Chinese and English languages with a context window length of 4096 tokens. It has achieved top results in several benchmarks. ## Facts - Repository: https://github.com/baichuan-inc/Baichuan-7B - Homepage: https://huggingface.co/baichuan-inc/baichuan-7B - Stars: 5,652 · Forks: 501 · Open issues: 88 · Watchers: 66 - Primary language: Python - License: Apache-2.0 - Last pushed: 2024-07-18T14:23:01+00:00 ## Categories - [LLM Frameworks](/categories/llm-frameworks.md) ## Tags llama, chinese, artificial-intelligence, large-language-models, gpt-4, chatgpt, huggingface, ceval ## Related tools - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,347) - [open-webui](/tools/open-webui-open-webui.md) - User-friendly AI Interface (Supports Ollama, OpenAI API, ...) (★ 144,575) - [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. (★ 116,702) - [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) - Implement a ChatGPT-like LLM in PyTorch from scratch (★ 98,711) - [TradingAgents](/tools/tauricresearch-tradingagents.md) - TradingAgents: Multi-Agents LLM Financial Trading Framework (★ 91,610) - [caveman](/tools/juliusbrussee-caveman.md) - Cuts 65% of tokens in AI coding agent responses. (★ 86,150) ## README (excerpt) ```text

Baichuan-7B

🤗 Hugging Face • 🤖 ModelScope • 💬 WeChat

中文 | English

# 更新信息 - [2023.09.06] 我们发布了新一代开源模型 [Baichuan 2](https://github.com/baichuan-inc/Baichuan2)，包含 7B、13B 尺寸 🔥🔥🔥 # 介绍 Baichuan-7B 是由百川智能开发的一个开源可商用的大规模预训练语言模型。基于 Transformer 结构，在大约 1.2 万亿 tokens 上训练的 70 亿参数模型，支持中英双语，上下文窗口长度为 4096。在标准的中文和英文 benchmark（C-Eval/MMLU）上均取得同尺寸最好的效果。 # 公开benchmark榜单 ## 中文评测 ### C-Eval [C-Eval 数据集](https://cevalbenchmark.com/index.html)是一个全面的中文基础模型评测数据集，涵盖了 52 个学科和四个难度的级别。我们使用该数据集的 dev 集作为 few-shot 的来源，在 test 集上进行了 `5-shot` 测试。通过执行执行下面的命令： ```bash cd evaluation python evaluate_zh.py --model_name_or_path 'your/model/path' ``` ### 结果 | Model 5-shot | Average | Avg(Hard) | STEM | Social Sciences | Humanities | Others | | :-------------------------: | :-----: | :-------: | :---: | :-------------: | :--------: | :----: | | GPT-4 | 68.7 | 54.9 | 67.1 | 77.6 | 64.5 | 67.8 | | ChatGPT | 54.4 | 41.4 | 52.9 | 61.8 | 50.9 | 53.6 | | Claude-v1.3 | 54.2 | 39.0 | 51.9 | 61.7 | 52.1 | 53.7 | | Claude-instant-v1.0 | 45.9 | 35.5 | 43.1 | 53.8 | 44.2 | 45.4 | | BLOOMZ-7B | 35.7 | 25.8 | 31.3 | 43.5 | 36.6 | 35.6 | | ChatGLM-6B | 34.5 | 23.1 | 30.4 | 39.6 | 37.4 | 34.5 | | Ziya-LLaMA-13B-pretrain | 30.2 | 22.7 | 27.7 | 34.4 | 32.0 | 28.9 | | moss-moon-003-base (16B) | 27.4 | 24.5 | 27.0 | 29.1 | 27.2 | 26.9 | | LLaMA-7B-hf | 27.1 | 25.9 | 27.1 | 26.8 | 27.9 | 26.3 | | Falcon-7B | 25.8 | 24.3 | 25.8 | 26.0 | 25.8 | 25.6 | | TigerBot-7B-base | 25.7 | 27.0 | 27.3 | 24.7 | 23.4 | 26.1 | | Aquila-7B* | 25.5 | 25.2 | 25.6 | 24.6 | 25.2 | 26.6 | | Open-LLaMA-v2-pretrain (7B) | 24.0 | 22.5 | 23.1 | 25.3 | 25.2 | 23.2 | | BLOOM-7B | 22.8 | 20.2 | 21.8 | 23.3 | 23.9 | 23.3 | | **Baichuan-7B** | 42.8 | 31.5 | 38.2 | 52.0 | 46.2 | 39.3 | ### Gaokao [Gaokao](https://github.com/OpenLMLab/GAOKAO-Bench) 是一个以中国高考题作为评测大语言模型能力的数据集，用以评估模型的语言能力和逻辑推理能力。 我们只保留了其中的单项选择题，随机划分后对所有模型进行统一 `5-shot` 测试。 ### 结果 以下是测试的结果。 | Model | Average | | :---------------------: | :-------: | | BLOOMZ-7B | 28.72 | | LLaMA-7B | 27.81 | | BLOOM-7B | 26.96 | | TigerBot-7B-base | 25.94 | | Falcon-7B | 23.98 | | Ziya-LLaMA-13B-pretrain | 23.17 | | ChatGLM-6B | 21.41 | | Open-LLaMA-v2-pretrain | 21.41 | | Aquila-7B* | 24.39 | | **Baichuan-7B** | **36.24** | ### AGIEval [AGIEval](https://github.com/microsoft/AGIEval) 旨在评估模型的认知和解决问题相关的任务中的一般能力。 我们只保留了其中的四选一单项选择题，随机划分后对所有模型进行了统一 `5-shot` 测试。 ### 结果 | Model | Average | | :---------------------: | :-------: | | BLOOMZ-7B | 30.27 | | LLaMA-7B | 28.17 | | Ziya-LLaMA-13B-pretrain | 27.64 | | Falcon-7B | 27.18 | | BLOOM-7B | 26.55 | | Aquila-7B* | 25.58 | ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/baichuan-inc-baichuan-7b`](/api/graphcanon/tools/baichuan-inc-baichuan-7b) - 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/_