Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+
+<div align="center">
+
+
+
+<h1>FireRedTTS-1S: An Upgraded Streamable Foundation
+Text-to-Speech System</h1>
+
+</div>
+
+#### 👉🏻 [FireRedTTS-1S Paper](https://arxiv.org/abs/2503.20499) 👈🏻
+#### 👉🏻 [FireRedTTS-1S Demos](https://fireredteam.github.io/demos/firered_tts_1s/) 👈🏻
+
+
+## News
+
+- [2025/05/26] 🔥 We add flow-mathing decoder and update the [technical report](https://arxiv.org/abs/2503.20499)
+- [2025/03/25] 🔥 We release the [technical report](https://arxiv.org/abs/2503.20499) and [project page](https://fireredteam.github.io/demos/firered_tts_1s/)
+
+## Roadmap
+
+- [x] 2025/04
+  - [x] Release the pre-trained checkpoints and inference code.
+  
+## Usage
+
+#### Clone and install
+
+- Clone the repo
+
+```shell
+https://github.com/FireRedTeam/FireRedTTS.git
+cd FireRedTTS
+```
+
+- Create conda env
+
+```shell
+# step1.create env
+conda create --name redtts python=3.10
+
+# stpe2.install torch （pytorch should match the cuda-version on your machine）
+# CUDA 11.8
+conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=11.8 -c pytorch -c nvidia
+# CUDA 12.1
+conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia
+
+# step3.install fireredtts form source
+cd fireredtts
+pip install -e . 
+
+# step4.install other requirements
+pip install -r requirements.txt
+```
+
+#### Download models
+
+Download the required model files from [**Model_Lists**](https://huggingface.co/FireRedTeam/FireRedTTS-1S/tree/main) and place them in the folder `pretrained_models`
+
+#### Basic Usage
+
+```python
+import os
+import torchaudio![alt text](image.png)
+from fireredtts.fireredtts import FireRedTTS
+
+# acoustic llm decoder
+tts = FireRedTTS(
+        config_path="configs/config_24k.json",
+        pretrained_path=<pretrained_models_dir>,
+  )
+
+
+"""
+# flow matching decoder
+tts = FireRedTTS(
+        config_path="configs/config_24k_flow.json",
+        pretrained_path=<pretrained_models_dir>,
+)
+"""
+
+#same language
+# For the test-hard evaluation, we enabled the use_tn=True configuration setting.
+rec_wavs = tts.synthesize(
+  prompt_wav="examples/prompt_1.wav",
+  prompt_text="对，所以说你现在的话，这个账单的话，你既然说能处理，那你就想办法处理掉。",
+  text="小红书，是中国大陆的网络购物和社交平台，成立于二零一三年六月。",
+  lang="zh",
+  use_tn=True
+)
+
+
+
+
+rec_wavs = rec_wavs.detach().cpu()
+out_wav_path = os.path.join("./example.wav")
+torchaudio.save(out_wav_path, rec_wavs, 24000)
+
+```
+
+## Tips
+
+- The reference audio should not be too long or too short; a duration of 3 to 10 seconds is recommended.
+- The reference audio should be smooth and natural, and the accompanying text must be accurate to enhance the stability and naturalness of the synthesized audio.
+
+
+## ⚠️ Usage Disclaimer ❗️❗️❗️❗️❗️❗️
+
+- The project incorporates zero-shot voice cloning functionality; Please note that this capability is intended **solely for academic research purposes**.
+- **DO NOT** use this model for **ANY illegal activities**❗️❗️❗️❗️❗️❗️
+- The developers assume no liability for any misuse of this model.
+- If you identify any instances of **abuse**, **misuse**, or **fraudulent** activities related to this project, **please report them to our team immediately.**
+