Kokoro-FastAPI 是一个基于 Docker 的 FastAPI 封装项目,用于 Kokoro-82M 文本到语音模型,支持 CPU ONNX 和 NVIDIA GPU PyTorch 加速,提供了自动拼接和处理功能。该项目支持 OpenAI - 兼容的API。 github 地址:GitHub - remsky/Kokoro-FastAPI: Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model ...
https://hf.co/hexgrad/Kokoro-82M. Contribute to ezyang/kokoro development by creating an account on GitHub.
Fork of https://huggingface.co/hexgrad/Kokoro-82M. Contribute to zboyles/Kokoro-82M development by creating an account on GitHub.
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这也是为什么,这个工作有人用Rust实现了。 Kokoros: Rust推理的Kokoro img 现在Rust推理版本已经推出。速度超快,还在等什么,赶紧下载下来玩一下! 相关地址: https://huggingface.co/hexgrad/Kokoro-82M Rust项目链接: https://github.com/lucasjinreal/Kokoros...
A simple wrapper on Kokoro-82M for easy usage. Contribute to RohanAwhad/kokoro-tts development by creating an account on GitHub.
git clone https://github.com/remsky/Kokoro-FastAPI.git cd Kokoro-FastAPI cd docker/gpu # For GPU support # or cd docker/cpu # For CPU support docker compose up --build # Models will auto-download, but if needed you can manually download: python docker/scripts/download_model.py --output...
git clone https://github.com/yakhyo/kokoro-82m.gitcdkokoro-82m Install dependencies: pip install -r requirements.txt Installespeakfor text-to-speech functionality: Linux: apt-get install espeak -y Docker docker build -t kokoro-docker.&&docker run --rm -p 7860:7860 kokoro-docker ...
Kokoro-82M拥有一个充满活力的 Discord 社区，用户可以寻求帮助、交流心得，并与其他开发者共同探讨和进步。社区还提供了多种资源链接以供参考：模型页面: https://image_url_1演示空间: https://image_url_2GitHub 仓库: https://image_url_3 这些资源帮助用户更深入地了解Kokoro-82M的细节，探索其强大的功能...
Kokoro-FastAPI地址:github.com/remsky/Kokor 在线体验与资源获取 用户可以通过 Hugging Face 平台访问 Kokoro 的在线演示,并下载模型权重和相关资源。 在线试用地址: huggingface.co/spaces/h 问题与挑战 可能是因为Kokoro TTS这个版本(0.23)刚支持中文的原因,现在Kokoro TTS中文速度很快,不过效果相对一般。而且中文分词...