172 lines
5.5 KiB
Markdown
172 lines
5.5 KiB
Markdown
<p align="center">
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<img src="https://github.com/josStorer/RWKV-Runner/assets/13366013/d24834b0-265d-45f5-93c0-fac1e19562af">
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</p>
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<h1 align="center">RWKV Runner</h1>
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<div align="center">
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本项目旨在消除大语言模型的使用门槛，全自动为你处理一切，你只需要一个仅仅几MB的可执行程序。此外本项目提供了与OpenAI
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API兼容的接口，这意味着一切ChatGPT客户端都是RWKV客户端。
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[![license][license-image]][license-url]
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[![release][release-image]][release-url]
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[English](README.md) | 简体中文
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### 安装
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[![Windows][Windows-image]][Windows-url]
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[![MacOS][MacOS-image]][MacOS-url]
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[![Linux][Linux-image]][Linux-url]
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[视频演示](https://www.bilibili.com/video/BV1hM4y1v76R) | [疑难解答](https://www.bilibili.com/read/cv23921171) | [预览](#Preview) | [下载][download-url] | [懒人包](https://pan.baidu.com/s/1wchIUHgne3gncIiLIeKBEQ?pwd=1111) | [服务器部署示例](https://github.com/josStorer/RWKV-Runner/tree/master/deploy-examples)
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[license-image]: http://img.shields.io/badge/license-MIT-blue.svg
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[license-url]: https://github.com/josStorer/RWKV-Runner/blob/master/LICENSE
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[release-image]: https://img.shields.io/github/release/josStorer/RWKV-Runner.svg
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[release-url]: https://github.com/josStorer/RWKV-Runner/releases/latest
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[download-url]: https://github.com/josStorer/RWKV-Runner/releases
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[Windows-image]: https://img.shields.io/badge/-Windows-blue?logo=windows
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[Windows-url]: https://github.com/josStorer/RWKV-Runner/blob/master/build/windows/Readme_Install.txt
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[MacOS-image]: https://img.shields.io/badge/-MacOS-black?logo=apple
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[MacOS-url]: https://github.com/josStorer/RWKV-Runner/blob/master/build/darwin/Readme_Install.txt
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[Linux-image]: https://img.shields.io/badge/-Linux-black?logo=linux
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[Linux-url]: https://github.com/josStorer/RWKV-Runner/blob/master/build/linux/Readme_Install.txt
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</div>
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#### 注意 目前RWKV中文模型质量一般，推荐使用英文模型或World(全球语言)体验实际RWKV能力
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#### 预设配置已经开启自定义CUDA算子加速，速度更快，且显存消耗更少。如果你遇到可能的兼容性问题，前往配置页面，关闭`使用自定义CUDA算子加速`
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#### 如果Windows Defender说这是一个病毒，你可以尝试下载[v1.0.8](https://github.com/josStorer/RWKV-Runner/releases/tag/v1.0.8)/[v1.0.9](https://github.com/josStorer/RWKV-Runner/releases/tag/v1.0.9)然后让其自动更新到最新版，或添加信任
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#### 对于不同的任务，调整API参数会获得更好的效果，例如对于翻译任务，你可以尝试设置Temperature为1，Top_P为0.3
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## 功能
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- RWKV模型管理，一键启动
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- 与OpenAI API完全兼容，一切ChatGPT客户端，都是RWKV客户端。启动模型后，打开 http://127.0.0.1:8000/docs 查看详细内容
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- 全自动依赖安装，你只需要一个轻巧的可执行程序
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- 预设了2G至32G显存的配置，几乎在各种电脑上工作良好
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- 自带用户友好的聊天和补全交互页面
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- 易于理解和操作的参数配置
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- 内置模型转换工具
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- 内置下载管理和远程模型检视
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- 多语言本地化
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- 主题切换
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- 自动更新
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## API并发压力测试
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```bash
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ab -p body.json -T application/json -c 20 -n 100 -l http://127.0.0.1:8000/chat/completions
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```
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body.json:
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```json
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{
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"messages": [
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{
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"role": "user",
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"content": "Hello"
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}
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]
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}
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```
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## Embeddings API 示例
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如果你在用langchain, 直接使用 `OpenAIEmbeddings(openai_api_base="http://127.0.0.1:8000", openai_api_key="sk-")`
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```python
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import numpy as np
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import requests
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def cosine_similarity(a, b):
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return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))
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values = [
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"I am a girl",
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"我是个女孩",
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"私は女の子です",
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"广东人爱吃福建人",
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"我是个人类",
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"I am a human",
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"that dog is so cute",
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"私はねこむすめです、にゃん♪",
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"宇宙级特大事件！号外号外！"
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]
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embeddings = []
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for v in values:
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r = requests.post("http://127.0.0.1:8000/embeddings", json={"input": v})
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embedding = r.json()["data"][0]["embedding"]
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embeddings.append(embedding)
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compared_embedding = embeddings[0]
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embeddings_cos_sim = [cosine_similarity(compared_embedding, e) for e in embeddings]
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for i in np.argsort(embeddings_cos_sim)[::-1]:
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print(f"{embeddings_cos_sim[i]:.10f} - {values[i]}")
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```
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## Todo
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- [ ] 模型训练功能
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- [x] CUDA算子int8提速
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- [x] macOS支持
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- [x] linux支持
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- [ ] 本地状态缓存数据库
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## 相关仓库:
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- RWKV-4-Raven: https://huggingface.co/BlinkDL/rwkv-4-raven/tree/main
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- ChatRWKV: https://github.com/BlinkDL/ChatRWKV
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- RWKV-LM: https://github.com/BlinkDL/RWKV-LM
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## Preview
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### 主页
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### 聊天
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### 补全
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### 配置
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### 模型管理
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### 下载管理
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### 设置
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