热门搜索:

fishaudio/fish-speech

fishaudio

Fish Speech官方容器镜像，用于部署和运行Fish Speech语音处理相关应用，提供官方支持的标准化运行环境。

16 次收藏下载次数: 0状态：社区镜像维护者：fishaudio仓库类型：镜像最近更新：21 天前

轩辕镜像，不浪费每一次拉取。点击查看

DockerHub 官方简介

轩辕镜像中文简介

标签下载

镜像标签列表与下载命令

轩辕镜像，不浪费每一次拉取。点击查看

Fish Speech

</a>
<a target="_blank" href="https://hub.docker.com/r/fishaudio/fish-speech">
    
</a>
<a target="_blank" href="[***]">
  
</a>

</a>
<a target="_blank" href="[***]">
    
</a>
<a target="_blank" href="[***]">
    
</a>

[!IMPORTANT] License Notice
This codebase is released under Apache License and all model weights are released under CC-BY-NC-SA-4.0 License. Please refer to LICENSE for more details.

[!WARNING] Legal 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.

Start Here

Here are the official documents for Fish Speech, follow the instructions to get started easily.

Installation
Inference
Samples

🎉 Announcement

We are excited to announce that we have rebranded to OpenAudio — introducing a revolutionary new series of advanced Text-to-Speech models that builds upon the foundation of Fish-Speech.

We are proud to release OpenAudio-S1 as the first model in this series, delivering significant improvements in quality, performance, and capabilities.

OpenAudio-S1 comes in two versions: OpenAudio-S1 and OpenAudio-S1-mini. Both models are now available on Fish Audio Playground (for OpenAudio-S1) and Hugging Face (for OpenAudio-S1-mini).

Visit the OpenAudio website for blog & tech report.

Highlights ✨

Excellent TTS quality

We use Seed TTS Eval Metrics to evaluate the model performance, and the results show that OpenAudio S1 achieves 0.008 WER and 0.004 CER on English text, which is significantly better than previous models. (English, auto eval, based on OpenAI gpt-4o-transcribe, speaker distance using Revai/pyannote-wespeaker-voxceleb-resnet34-LM)

Model	Word Error Rate (WER)	Character Error Rate (CER)	Speaker Distance
S1	0.008	0.004	0.332
S1-mini	0.011	0.005	0.380

Best Model in TTS-Arena2 🏆

OpenAudio S1 has achieved the #1 ranking on TTS-Arena2, the benchmark for text-to-speech evaluation:

Speech Control

OpenAudio S1 supports a variety of emotional, tone, and special markers to enhance speech synthesis:

Basic emotions:

(angry) (sad) (excited) (surprised) (satisfied) (delighted) 
(scared) (worried) (upset) (nervous) (frustrated) (depressed)
(empathetic) (embarrassed) (disgusted) (moved) (proud) (relaxed)
(grateful) (confident) (interested) (curious) (confused) (joyful)

Advanced emotions:

(disdainful) (unhappy) (anxious) (hysterical) (indifferent) 
(impatient) (guilty) (scornful) (panicked) (furious) (reluctant)
(keen) (disapproving) (negative) (denying) (astonished) (serious)
(sarcastic) (conciliative) (comforting) (sincere) (sneering)
(hesitating) (yielding) (painful) (awkward) (amused)

Tone markers:

(in a hurry tone) (shouting) (screaming) (whispering) (soft tone)

Special audio effects:

(laughing) (chuckling) (sobbing) (crying loudly) (sighing) (panting)
(groaning) (crowd laughing) (background laughter) (audience laughing)

You can also use Ha,ha,ha to control, there's many other cases waiting to be explored by yourself.

(Support for English, Chinese and Japanese now, and more languages is coming soon!)

Two Type of Models

Model	Size	Availability	Features
S1	4B parameters	Avaliable on fish.audio	Full-featured flagship model
S1-mini	0.5B parameters	Avaliable on huggingface hf space	Distilled version with core capabilities

Both S1 and S1-mini incorporate online Reinforcement Learning from Human Feedback (RLHF).

Features

Zero-shot & Few-shot TTS: Input a 10 to 30-second vocal sample to generate high-quality TTS output. For detailed guidelines, see Voice Cloning Best Practices.

Multilingual & Cross-lingual Support: Simply copy and paste multilingual text into the input box—no need to worry about the language. Currently supports English, Japanese, Korean, Chinese, French, German, Arabic, and Spanish.

No Phoneme Dependency: The model has strong generalization capabilities and does not rely on phonemes for TTS. It can handle text in any language script.

Highly Accurate: Achieves a low CER (Character Error Rate) of around 0.4% and WER (Word Error Rate) of around 0.8% for Seed-TTS Eval.

Fast: Accelerated by torch compile, the real-time factor is approximately 1:7 on an Nvidia RTX 4090 GPU.

WebUI Inference: Features an easy-to-use, Gradio-based web UI compatible with Chrome, Firefox, Edge, and other browsers.

GUI Inference: Offers a PyQt6 graphical interface that works seamlessly with the API server. Supports Linux, Windows, and macOS. https://github.com/AnyaCoder/fish-speech-gui.
Deploy-Friendly: Easily set up an inference server with native support for Linux, Windows (MacOS comming soon), minimizing speed loss.

Media & Demos

Social Media

Interactive Demos

Video Showcases

Audio Samples

High-quality audio samples will be available soon, demonstrating our multilingual TTS capabilities across different languages and emotions.

Credits

https://github.com/daniilrobnikov/vits2
https://github.com/fishaudio/Bert-VITS2
https://github.com/innnky/gpt-vits
https://github.com/b04901014/MQTTS
https://github.com/pytorch-labs/gpt-fast
https://github.com/RVC-Boss/GPT-SoVITS
https://github.com/QwenLM/Qwen3

Tech Report (V1.4)

bibtex
@misc{fish-speech-v1.4,
      title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis},
      author={Shijia Liao and Yuxuan Wang and Tianyu Li and Yifan Cheng and Ruoyi Zhang and Rongzhi Zhou and Yijin Xing},
      year={2024},
      eprint={2411.01156},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2411.01156},
}

镜像拉取方式

您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问标签列表页面。

轩辕镜像加速拉取命令点我查看更多 fish-speech 镜像标签

docker pull docker.xuanyuan.run/fishaudio/fish-speech:<标签>

使用方法：

DockerHub 原生拉取命令

docker pull fishaudio/fish-speech:<标签>

轩辕镜像配置手册

探索更多轩辕镜像的使用方法，找到最适合您系统的配置方式

Docker 配置

登录仓库拉取

通过 Docker 登录认证访问私有仓库

专属域名拉取

无需登录使用专属域名

K8s Containerd

Kubernetes 集群配置 Containerd

K3s

K3s 轻量级 Kubernetes 镜像加速

Dev Containers

VS Code Dev Containers 配置

Podman

Podman 容器引擎配置

Singularity/Apptainer

HPC 科学计算容器配置

其他仓库配置

ghcr、Quay、nvcr 等镜像仓库

Harbor 镜像源配置

Harbor Proxy Repository 对接专属域名

Portainer 镜像源配置

Portainer Registries 加速拉取

Nexus 镜像源配置

Nexus3 Docker Proxy 内网缓存

系统配置

Linux

在 Linux 系统配置镜像服务

Windows/Mac

在 Docker Desktop 配置镜像

MacOS OrbStack

MacOS OrbStack 容器配置

Docker Compose

Docker Compose 项目配置

NAS 设备

群晖

Synology 群晖 NAS 配置

飞牛

飞牛 fnOS 系统配置镜像

绿联

绿联 NAS 系统配置镜像

威联通

QNAP 威联通 NAS 配置

极空间

极空间 NAS 系统配置服务

网络设备

爱快路由

爱快 iKuai 路由系统配置

宝塔面板

在宝塔面板一键配置镜像

需要其他帮助？请查看我们的常见问题Docker 镜像访问常见问题解答或提交工单

镜像拉取常见问题

使用与功能问题

配置了专属域名后，docker search 为什么会报错？

docker search 限制

Docker Hub 上有的镜像，为什么在轩辕镜像网站搜不到？

站内搜不到镜像

机器不能直连外网时，怎么用 docker save / load 迁镜像？

离线 save/load

docker pull 拉插件报错（plugin v1+json）怎么办？

插件要用 plugin install

WSL 里 Docker 拉镜像特别慢，怎么排查和优化？

WSL 拉取慢

轩辕镜像安全吗？如何用 digest 校验镜像没被篡改？

安全与 digest

第一次用轩辕镜像拉 Docker 镜像，要怎么登录和配置？

新手拉取配置

轩辕镜像合规吗？轩辕镜像的合规是怎么做的？

镜像合规机制

错误码与失败问题

docker pull 提示 manifest unknown 怎么办？

manifest unknown

docker pull 提示 no matching manifest 怎么办？

no matching manifest（架构）

镜像已拉取完成，却提示 invalid tar header 或 failed to register layer 怎么办？

invalid tar header（解压）

Docker pull 时 HTTPS / TLS 证书验证失败怎么办？

TLS 证书失败

Docker pull 时 DNS 解析超时或连不上仓库怎么办？

DNS 超时

docker 无法连接轩辕镜像域名怎么办？

域名连通性排查

Docker 拉取出现 410 Gone 怎么办？

410 Gone 排查

出现 402 或「流量用尽」提示怎么办？

402 与流量用尽

Docker 拉取提示 UNAUTHORIZED（401）怎么办？

401 认证失败

遇到 429 Too Many Requests（请求太频繁）怎么办？

429 限流

docker login 提示 Cannot autolaunch D-Bus，还算登录成功吗？

D-Bus 凭证提示

为什么会出现「单层超过 20GB」或 413，无法加速拉取？

413 与超大单层

账号 / 计费 / 权限

轩辕镜像免费版和专业版有什么区别？

免费版与专业版区别

轩辕镜像支持哪些 Docker 镜像仓库？

支持的镜像仓库

镜像拉取失败还会不会扣流量？

失败是否计费

麒麟 V10 / 统信 UOS 提示 KYSEC 权限不够怎么办？

KYSEC 拦截脚本

如何在轩辕镜像申请开具发票？

申请开票

怎么修改轩辕镜像的网站登录和仓库登录密码？

修改登录密码

如何注销轩辕镜像账户？要注意什么？

注销账户

配置与原理类

写了 registry-mirrors，为什么还是走官方或仍然报错？

mirrors 不生效

怎么用 docker tag 去掉镜像名里的轩辕域名前缀？

去掉域名前缀

如何拉取指定 CPU 架构的镜像（如 ARM64、AMD64）？

指定架构拉取

用轩辕镜像拉镜像时快时慢，常见原因有哪些？

拉取速度原因

查看全部问题→

用户好评

来自真实用户的反馈，见证轩辕镜像的优质服务

oldzhang

运维工程师

Linux服务器

"Docker访问体验非常流畅，大镜像也能快速完成下载。"

热门搜索:

fishaudio/fish-speech

fishaudio

Fish Speech官方容器镜像，用于部署和运行Fish Speech语音处理相关应用，提供官方支持的标准化运行环境。

16 次收藏下载次数: 0状态：社区镜像维护者：fishaudio仓库类型：镜像最近更新：21 天前

轩辕镜像，不浪费每一次拉取。点击查看

DockerHub 官方简介

轩辕镜像中文简介

标签下载

镜像标签列表与下载命令

轩辕镜像，不浪费每一次拉取。点击查看

Fish Speech

</a>
<a target="_blank" href="https://hub.docker.com/r/fishaudio/fish-speech">
    
</a>
<a target="_blank" href="[***]">
  
</a>

</a>
<a target="_blank" href="[***]">
    
</a>
<a target="_blank" href="[***]">
    
</a>

[!IMPORTANT] License Notice
This codebase is released under Apache License and all model weights are released under CC-BY-NC-SA-4.0 License. Please refer to LICENSE for more details.

[!WARNING] Legal 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.

Start Here

Here are the official documents for Fish Speech, follow the instructions to get started easily.

Installation
Inference
Samples

🎉 Announcement

We are excited to announce that we have rebranded to OpenAudio — introducing a revolutionary new series of advanced Text-to-Speech models that builds upon the foundation of Fish-Speech.

We are proud to release OpenAudio-S1 as the first model in this series, delivering significant improvements in quality, performance, and capabilities.

Visit the OpenAudio website for blog & tech report.

Highlights ✨

Excellent TTS quality

Model	Word Error Rate (WER)	Character Error Rate (CER)	Speaker Distance
S1	0.008	0.004	0.332
S1-mini	0.011	0.005	0.380

Best Model in TTS-Arena2 🏆

OpenAudio S1 has achieved the #1 ranking on TTS-Arena2, the benchmark for text-to-speech evaluation:

Speech Control

OpenAudio S1 supports a variety of emotional, tone, and special markers to enhance speech synthesis:

Basic emotions:

(angry) (sad) (excited) (surprised) (satisfied) (delighted) 
(scared) (worried) (upset) (nervous) (frustrated) (depressed)
(empathetic) (embarrassed) (disgusted) (moved) (proud) (relaxed)
(grateful) (confident) (interested) (curious) (confused) (joyful)

Advanced emotions:

(disdainful) (unhappy) (anxious) (hysterical) (indifferent) 
(impatient) (guilty) (scornful) (panicked) (furious) (reluctant)
(keen) (disapproving) (negative) (denying) (astonished) (serious)
(sarcastic) (conciliative) (comforting) (sincere) (sneering)
(hesitating) (yielding) (painful) (awkward) (amused)

Tone markers:

(in a hurry tone) (shouting) (screaming) (whispering) (soft tone)

Special audio effects:

(laughing) (chuckling) (sobbing) (crying loudly) (sighing) (panting)
(groaning) (crowd laughing) (background laughter) (audience laughing)

You can also use Ha,ha,ha to control, there's many other cases waiting to be explored by yourself.

(Support for English, Chinese and Japanese now, and more languages is coming soon!)

Two Type of Models

Model	Size	Availability	Features
S1	4B parameters	Avaliable on fish.audio	Full-featured flagship model
S1-mini	0.5B parameters	Avaliable on huggingface hf space	Distilled version with core capabilities

Both S1 and S1-mini incorporate online Reinforcement Learning from Human Feedback (RLHF).

Features

Zero-shot & Few-shot TTS: Input a 10 to 30-second vocal sample to generate high-quality TTS output. For detailed guidelines, see Voice Cloning Best Practices.

No Phoneme Dependency: The model has strong generalization capabilities and does not rely on phonemes for TTS. It can handle text in any language script.

Highly Accurate: Achieves a low CER (Character Error Rate) of around 0.4% and WER (Word Error Rate) of around 0.8% for Seed-TTS Eval.

Fast: Accelerated by torch compile, the real-time factor is approximately 1:7 on an Nvidia RTX 4090 GPU.

WebUI Inference: Features an easy-to-use, Gradio-based web UI compatible with Chrome, Firefox, Edge, and other browsers.

GUI Inference: Offers a PyQt6 graphical interface that works seamlessly with the API server. Supports Linux, Windows, and macOS. https://github.com/AnyaCoder/fish-speech-gui.
Deploy-Friendly: Easily set up an inference server with native support for Linux, Windows (MacOS comming soon), minimizing speed loss.

Media & Demos

Social Media

Interactive Demos

Video Showcases

Audio Samples

High-quality audio samples will be available soon, demonstrating our multilingual TTS capabilities across different languages and emotions.

Credits

https://github.com/daniilrobnikov/vits2
https://github.com/fishaudio/Bert-VITS2
https://github.com/innnky/gpt-vits
https://github.com/b04901014/MQTTS
https://github.com/pytorch-labs/gpt-fast
https://github.com/RVC-Boss/GPT-SoVITS
https://github.com/QwenLM/Qwen3

Tech Report (V1.4)

bibtex
@misc{fish-speech-v1.4,
      title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis},
      author={Shijia Liao and Yuxuan Wang and Tianyu Li and Yifan Cheng and Ruoyi Zhang and Rongzhi Zhou and Yijin Xing},
      year={2024},
      eprint={2411.01156},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2411.01156},
}

镜像拉取方式

您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问标签列表页面。

轩辕镜像加速拉取命令点我查看更多 fish-speech 镜像标签

docker pull docker.xuanyuan.run/fishaudio/fish-speech:<标签>

使用方法：

DockerHub 原生拉取命令

docker pull fishaudio/fish-speech:<标签>

轩辕镜像配置手册

探索更多轩辕镜像的使用方法，找到最适合您系统的配置方式

Docker 配置

登录仓库拉取

通过 Docker 登录认证访问私有仓库

专属域名拉取

无需登录使用专属域名

K8s Containerd

Kubernetes 集群配置 Containerd

K3s

K3s 轻量级 Kubernetes 镜像加速

Dev Containers

VS Code Dev Containers 配置

Podman

Podman 容器引擎配置

Singularity/Apptainer

HPC 科学计算容器配置

其他仓库配置

ghcr、Quay、nvcr 等镜像仓库

Harbor 镜像源配置

Harbor Proxy Repository 对接专属域名

Portainer 镜像源配置

Portainer Registries 加速拉取

Nexus 镜像源配置

Nexus3 Docker Proxy 内网缓存

系统配置

Linux

在 Linux 系统配置镜像服务

Windows/Mac

在 Docker Desktop 配置镜像

MacOS OrbStack

MacOS OrbStack 容器配置

Docker Compose

Docker Compose 项目配置

NAS 设备

群晖

Synology 群晖 NAS 配置

飞牛

飞牛 fnOS 系统配置镜像

绿联

绿联 NAS 系统配置镜像

威联通

QNAP 威联通 NAS 配置

极空间

极空间 NAS 系统配置服务

网络设备

爱快路由

爱快 iKuai 路由系统配置

宝塔面板

在宝塔面板一键配置镜像

需要其他帮助？请查看我们的常见问题Docker 镜像访问常见问题解答或提交工单

镜像拉取常见问题

使用与功能问题

配置了专属域名后，docker search 为什么会报错？

docker search 限制

Docker Hub 上有的镜像，为什么在轩辕镜像网站搜不到？

站内搜不到镜像

机器不能直连外网时，怎么用 docker save / load 迁镜像？

离线 save/load

docker pull 拉插件报错（plugin v1+json）怎么办？

插件要用 plugin install

WSL 里 Docker 拉镜像特别慢，怎么排查和优化？

WSL 拉取慢

轩辕镜像安全吗？如何用 digest 校验镜像没被篡改？

安全与 digest

第一次用轩辕镜像拉 Docker 镜像，要怎么登录和配置？

新手拉取配置

轩辕镜像合规吗？轩辕镜像的合规是怎么做的？

镜像合规机制

错误码与失败问题

docker pull 提示 manifest unknown 怎么办？

manifest unknown

docker pull 提示 no matching manifest 怎么办？

no matching manifest（架构）

镜像已拉取完成，却提示 invalid tar header 或 failed to register layer 怎么办？

invalid tar header（解压）

Docker pull 时 HTTPS / TLS 证书验证失败怎么办？

TLS 证书失败

Docker pull 时 DNS 解析超时或连不上仓库怎么办？

DNS 超时

docker 无法连接轩辕镜像域名怎么办？

域名连通性排查

Docker 拉取出现 410 Gone 怎么办？

410 Gone 排查

出现 402 或「流量用尽」提示怎么办？

402 与流量用尽

Docker 拉取提示 UNAUTHORIZED（401）怎么办？

401 认证失败

遇到 429 Too Many Requests（请求太频繁）怎么办？

429 限流

docker login 提示 Cannot autolaunch D-Bus，还算登录成功吗？

D-Bus 凭证提示

为什么会出现「单层超过 20GB」或 413，无法加速拉取？

413 与超大单层

账号 / 计费 / 权限

轩辕镜像免费版和专业版有什么区别？

免费版与专业版区别

轩辕镜像支持哪些 Docker 镜像仓库？

支持的镜像仓库

镜像拉取失败还会不会扣流量？

失败是否计费

麒麟 V10 / 统信 UOS 提示 KYSEC 权限不够怎么办？

KYSEC 拦截脚本

如何在轩辕镜像申请开具发票？

申请开票

怎么修改轩辕镜像的网站登录和仓库登录密码？

修改登录密码

如何注销轩辕镜像账户？要注意什么？

注销账户

配置与原理类

写了 registry-mirrors，为什么还是走官方或仍然报错？

mirrors 不生效

怎么用 docker tag 去掉镜像名里的轩辕域名前缀？

去掉域名前缀

如何拉取指定 CPU 架构的镜像（如 ARM64、AMD64）？

指定架构拉取

用轩辕镜像拉镜像时快时慢，常见原因有哪些？

拉取速度原因

查看全部问题→

用户好评

来自真实用户的反馈，见证轩辕镜像的优质服务

oldzhang

运维工程师

Linux服务器

"Docker访问体验非常流畅，大镜像也能快速完成下载。"

fishaudio/fish-speech

Fish Speech官方容器镜像，用于部署和运行Fish Speech语音处理相关应用，提供官方支持的标准化运行环境。

Fish Speech

Start Here

🎉 Announcement

Highlights ✨

Excellent TTS quality

Best Model in TTS-Arena2 🏆

Speech Control

Two Type of Models

Features

Media & Demos

Social Media

Interactive Demos

Video Showcases

Audio Samples

Credits

Tech Report (V1.4)

更多相关 Docker 镜像与资源

镜像拉取方式

轩辕镜像加速拉取命令点我查看更多 fish-speech 镜像标签

DockerHub 原生拉取命令

更多 fish-speech 镜像推荐

library/glassfish

atlassian/fisheye

islandora/crayfish

airbyte/source-fish

biocontainers/jellyfish

intel/speech-generation

查看更多 fish-speech 相关镜像

轩辕镜像配置手册

Docker 配置

登录仓库拉取

专属域名拉取

K8s Containerd

K3s

Dev Containers

Podman

Singularity/Apptainer

其他仓库配置

Harbor 镜像源配置

Portainer 镜像源配置

Nexus 镜像源配置

系统配置

Linux

Windows/Mac

MacOS OrbStack

Docker Compose

NAS 设备

群晖

飞牛

绿联

威联通

极空间

网络设备

爱快路由

宝塔面板

镜像拉取常见问题

使用与功能问题

配置了专属域名后，docker search 为什么会报错？

Docker Hub 上有的镜像，为什么在轩辕镜像网站搜不到？

机器不能直连外网时，怎么用 docker save / load 迁镜像？

docker pull 拉插件报错（plugin v1+json）怎么办？

WSL 里 Docker 拉镜像特别慢，怎么排查和优化？

轩辕镜像安全吗？如何用 digest 校验镜像没被篡改？

第一次用轩辕镜像拉 Docker 镜像，要怎么登录和配置？

轩辕镜像合规吗？轩辕镜像的合规是怎么做的？

错误码与失败问题

docker pull 提示 manifest unknown 怎么办？

docker pull 提示 no matching manifest 怎么办？

镜像已拉取完成，却提示 invalid tar header 或 failed to register layer 怎么办？

Docker pull 时 HTTPS / TLS 证书验证失败怎么办？

Docker pull 时 DNS 解析超时或连不上仓库怎么办？

docker 无法连接轩辕镜像域名怎么办？

Docker 拉取出现 410 Gone 怎么办？

出现 402 或「流量用尽」提示怎么办？

Docker 拉取提示 UNAUTHORIZED（401）怎么办？

遇到 429 Too Many Requests（请求太频繁）怎么办？

docker login 提示 Cannot autolaunch D-Bus，还算登录成功吗？

为什么会出现「单层超过 20GB」或 413，无法加速拉取？