Update readme

README.md

@@ -1,6 +1,17 @@
 # Fish Speech
 
-This repo is still under construction. Please check back later.
+[中文文档](README.zh.md)
+
+This codebase is released under BSD-3-Clause License, and all models are released under CC-BY-NC-SA-4.0 License. Please refer to [LICENSE](LICENSE) for more details. 
+
+## Disclaimer
+We do not hold any responsibility for any illegal usage of the codebase. Please refer to your local laws about DMCA and other related laws.
+
+## Requirements
+- GPU memory: 4GB (for inference), 24GB (for finetuning)
+- System: Linux (full functionality), Windows (inference only, flash-attn is not supported, torch.compile is not supported)
+
+Therefore, we strongly recommend to use WSL2 or docker to run the codebase for Windows users.
 
 ## Setup
 ```bash
@@ -16,6 +27,25 @@ pip3 install ninja && MAX_JOBS=4 pip3 install flash-attn --no-build-isolation
 pip3 install -e .
 ```
 
+## Inference (CLI)
+Download required `vqgan` and `text2semantic` model from our huggingface repo.
+
+```bash
+TODO
+```
+
+Generate semantic tokens from text:
+```bash
+python tools/llama/generate.py
+```
+
+You may want to use `--compile` to fuse cuda kernels faster inference (~25 tokens/sec -> ~300 tokens/sec).
+
+Generate vocals from semantic tokens:
+```bash
+python tools/vqgan/inference.py -i codes_0.npy
+```
+
 ## Rust Data Server
 Since loading and shuffle the dataset is very slow and memory consuming, we use a rust server to load and shuffle the dataset. The server is based on GRPC and can be installed by
 

README.zh.md

@@ -0,0 +1,61 @@
+# Fish Speech
+
+此代码库根据 BSD-3-Clause 许可证发布，所有模型根据 CC-BY-NC-SA-4.0 许可证发布。请参阅 [LICENSE](LICENSE) 了解更多细节。
+
+## 免责声明
+我们不对代码库的任何非法使用承担任何责任。请参阅您当地关于DMCA和其他相关法律的法律。
+
+## 要求
+- GPU内存：4GB（用于推理），24GB（用于微调）
+- 系统：Linux（全部功能），Windows（仅推理，不支持flash-attn，不支持torch.compile）
+
+因此，我们强烈建议Windows用户使用WSL2或docker来运行代码库。
+
+## 设置
+```bash
+# 基本环境设置
+conda create -n fish-speech python=3.10
+conda activate fish-speech
+conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
+
+# 安装 flash-attn（适用于linux）
+pip3 install ninja && MAX_JOBS=4 pip3 install flash-attn --no-build-isolation
+
+# 安装 fish-speech
+pip3 install -e .
+```
+
+## 推理（CLI）
+
+从我们的 huggingface 仓库下载所需的 `vqgan` 和 `text2semantic` 模型。
+    
+```bash
+TODO
+```
+
+从文本生成语义 token：
+```bash
+python tools/llama/generate.py
+```
+
+您可能希望使用 `--compile` 来融合 cuda 内核以实现更快的推理（~25 个 token/秒 -> ~300 个 token/秒）。
+
+从语义 token 生成人声：
+```bash
+python tools/vqgan/inference.py -i codes_0.npy
+```
+
+## Rust 数据服务器
+由于加载和洗牌数据集非常缓慢且占用内存，因此我们使用 rust 服务器来加载和洗牌数据集。该服务器基于 GRPC，可以通过以下方式安装
+
+```bash
+cd data_server
+cargo build --release
+```
+
+## 致谢
+- [VITS2 (daniilrobnikov)](https://github.com/daniilrobnikov/vits2)
+- [Bert-VITS2](https://github.com/fishaudio/Bert-VITS2)
+- [GPT VITS](https://github.com/innnky/gpt-vits)
+- [MQTTS](https://github.com/b04901014/MQTTS)
+- [GPT Fast](https://github.com/pytorch-labs/gpt-fast)