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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A 13B large language model developed by Baichuan Intelligent Technology
| Date | Stars |
|---|---|
| 2026-07-24 | 2930 |
| 2026-07-25 | 2930 |
| 2026-07-28 | 2930 |
| 2026-07-30 | 2930 |
| 2026-07-31 | 2931 |
| 2026-08-06 | 2931 |
Today
— stars today
This week
+1 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.03%/day
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Baichuan-13B
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🤗 <a href="https://huggingface.co/baichuan-inc/Baichuan-13B-Base" target="_blank">Baichuan-13B-Base</a>
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🤗 <a href="https://huggingface.co/baichuan-inc/Baichuan-13B-Chat" target="_blank">Baichuan-13B-Chat</a>
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🤖 <a href="https://modelscope.cn/organization/baichuan-inc" target="_blank">ModelScope</a>
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💬 <a href="https://github.com/baichuan-inc/Baichuan-13B/blob/main/media/wechat.jpeg?raw=true" target="_blank">WeChat</a>
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[](https://github.com/Baichuan-inc/baichuan-13B/blob/main/LICENSE)
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<b>中文</b> |
<a href="https://github.com/baichuan-inc/Baichuan-13B/blob/main/README_EN.md">English</a>
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# 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 🔥🔥🔥
- [2023.08.01] 更新了对齐模型 [Baichuan-13B-Chat](https://huggingface.co/baichuan-inc/Baichuan-13B-Chat) 权重，优化了部分场景的效果
# 目录
- [介绍](#介绍)
- [Benchmark结果](#Benchmark结果)
- [模型细节](#模型细节)
- [推理和部署](#推理和部署)
- [对模型进行微调](#对模型进行微调)
- [声明](#声明)
- [协议](#协议)
# 介绍
Baichuan-13B 是由百川智能继 [Baichuan-7B](https://github.com/baichuan-inc/baichuan-7B) 之后开发的包含 130 亿参数的开源可商用的大规模语言模型，在权威的中文和英文 benchmark 上均取得同尺寸最好的效果。本次发布包含有预训练 ([Baichuan-13B-Base](https://huggingface.co/baichuan-inc/Baichuan-13B-Base)) 和对齐 ([Baichuan-13B-Chat](https://huggingface.co/baichuan-inc/Baichuan-13B-Chat)) 两个版本。Baichuan-13B 有如下几个特点：
1. **更大尺寸、更多数据**：Baichuan-13B 在 [Baichuan-7B](https://github.com/baichuan-inc/baichuan-7B) 的基础上进一步扩大参数量到 130 亿，并且在高质量的语料上训练了 1.4 万亿 tokens，超过 LLaMA-13B 40%，是当前开源 13B 尺寸下训练数据量最多的模型。支持中英双语，使用 ALiBi 位置编码，上下文窗口长度为 4096。
2. **同时开源预训练和对齐模型**：预训练模型是适用开发者的『 基座 』，而广大普通用户对有对话功能的对齐模型具有更强的需求。因此本次开源我们同时发布了对齐模型（Baichuan-13B-Chat），具有很强的对话能力，开箱即用，几行代码即可简单的部署。
3. **更高效的推理**：为了支持更广大用户的使用，我们本次同时开源了 int8 和 int4 的量化版本，相对非量化版本在几乎没有效果损失的情况下大大降低了部署的机器资源门槛，可以部署在如 Nvidia 3090 这样的消费级显卡上。
4. **开源免费可商用**：Baichuan-13B 不仅对学术研究完全开放，开发者也仅需邮件申请并获得官方商用许可后，即可以免费商用。
# Benchmark结果
我们在各个权威大语言模型的中英文 benchmark 上进行了`5-shot`评测。结果如下：
## [C-Eval](https://cevalbenchmark.com/index.html#home)
| Model 5-shot | STEM | Social Sciences | Humanities | Others | Average |
|-------------------------|:-----:|:---------------:|:----------:|:------:|:-------:|
| Baichuan-7B | 38.2 | 52.0 | 46.2 | 39.3 | 42.8 |
| Chinese-Alpaca-Plus-13B | 35.2 | 45.6 | 40.0 | 38.2 | 38.8 |
| Vicuna-13B | 30.5 | 38.2 | 32.5 | 32.5 | 32.8 |
| Chinese-LLaMA-Plus-13B | 30.3 | 38.0 | 32.9 | 29.1 | 32.1 |
| Ziya-LLaMA-13B-Pretrain | 27.6 | 34.4 | 32.0 | 28.6 | 30.0 |
| LLaMA-13B | 27.0 | 33.6 | 27.7 | 27.6 | 28.5 |
| moss-moon-003-base (16B)| 27.0 | 29.1 | 27.2 | 26.9 | 27.4 |
| **Baichuan-13B-Base** | **45.9** | **63.5** | **57.2** | **49.3** | **52.4** |
| **Baichuan-13B-Chat** | **43.7** | **64.6** | **56.2** | **49.2** | **51.5** |
## [MMLU](https://arxiv.org/abs/2009.03300)
| Model 5-shot | STEM | Social Sciences | Humanities | Others | Average |
|-------------------------|:-----:|:---------------:|:----------:|:------:|:-------:|
| Vicuna-13B | 40.4 | 60.5 | 49.5 | 58.4 | 52.0 |
| LLaMA-13B | 36.1 | 53.0 | 44.0 | 52.8 | 46.3 |
| Chinese-Alpaca-Plus-13B | 36.9 | 48.9 | 40.5 | 50.5 | 43.9 |
| Ziya-LLaMA-13B-Pretrain | 35.6 | 47.6 | 40.1 | 49.4 | 42.9 |
| Baichuan-7B | 35.6 | 48.9 | 38.4 | 48.1 | 42.3 |
| Chinese-LLaMA-Plus-13B | 33.1 | 42.8 | 37.0 | 44.6 | 39.2 |
| moss-moon-003-base (16Excerpt of 16,955 characters
Read on GitHub
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LoveSJ · Baichuan Inc. · China
3
GuoPD · Baichuan Intelligent Technology · China
2
1
AdonisHong · VSK Tech · China
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:00faf0e38388d55d, topic:large-language-models
matched fp:00faf0e38388d55d, topic:natural-language-processing
matched fp:00faf0e38388d55d, topic:benchmark
matched fp:00faf0e38388d55d, topic:chatgpt