up

README - 副本.md

@@ -0,0 +1,190 @@
+<div align="center">
+
+<h1>GPT-SoVITS-WebUI</h1>
+A Powerful Few-shot Voice Conversion and Text-to-Speech WebUI.<br><br>
+
+[![madewithlove](https://img.shields.io/badge/made_with-%E2%9D%A4-red?style=for-the-badge&labelColor=orange
+)](https://github.com/RVC-Boss/GPT-SoVITS)
+
+<img src="https://counter.seku.su/cmoe?name=gptsovits&theme=r34" /><br>
+
+[![Licence](https://img.shields.io/badge/LICENSE-MIT-green.svg?style=for-the-badge)](https://github.com/RVC-Boss/GPT-SoVITS/blob/main/LICENSE)
+[![Huggingface](https://img.shields.io/badge/🤗%20-Spaces-yellow.svg?style=for-the-badge)](https://huggingface.co/lj1995/GPT-SoVITS/tree/main)
+
+
+[**English**](./README.md) | [**中文简体**](./docs/cn/README.md) | [**日本語**](./docs/ja/README.md)
+
+</div>
+
+------
+
+
+
+> Check out our [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw) here!
+
+https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb
+
+## Features:
+1. **Zero-shot TTS:** Input a 5-second vocal sample and experience instant text-to-speech conversion.
+
+2. **Few-shot TTS:** Fine-tune the model with just 1 minute of training data for improved voice similarity and realism.
+
+3. **Cross-lingual Support:** Inference in languages different from the training dataset, currently supporting English, Japanese, and Chinese.
+
+4. **WebUI Tools:** Integrated tools include voice accompaniment separation, automatic training set segmentation, Chinese ASR, and text labeling, assisting beginners in creating training datasets and GPT/SoVITS models.
+
+## Environment Preparation
+
+If you are a Windows user (tested with win>=10) you can install directly via the prezip. Just download the [prezip](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true), unzip it and double-click go-webui.bat to start GPT-SoVITS-WebUI.
+
+### Tested Environments
+
+- Python 3.9, PyTorch 2.0.1, CUDA 11
+- Python 3.10.13, PyTorch 2.1.2, CUDA 12.3
+
+_Note: numba==0.56.4 require py<3.11_
+
+### Quick Install with Conda
+
+```bash
+conda create -n GPTSoVits python=3.9
+conda activate GPTSoVits
+bash install.sh
+```
+### Install Manually
+
+#### Pip Packages
+
+```bash
+pip install torch numpy scipy tensorboard librosa==0.9.2 numba==0.56.4 pytorch-lightning gradio==3.14.0 ffmpeg-python onnxruntime tqdm cn2an pypinyin pyopenjtalk g2p_en chardet transformers jieba_fast
+```
+
+#### Additional Requirements
+
+If you need Chinese ASR (supported by FunASR), install:
+
+```bash
+pip install modelscope torchaudio sentencepiece funasr
+```
+
+#### FFmpeg
+
+##### Conda Users
+```bash
+conda install ffmpeg
+```
+
+##### Ubuntu/Debian Users
+
+```bash
+sudo apt install ffmpeg
+sudo apt install libsox-dev
+conda install -c conda-forge 'ffmpeg<7'
+```
+
+##### MacOS Users
+
+```bash
+brew install ffmpeg
+```
+
+##### Windows Users
+
+Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) and [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) in the GPT-SoVITS root.
+
+### Pretrained Models
+
+
+Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS/pretrained_models`.
+
+For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/damo_asr/models`.
+
+For UVR5 (Vocals/Accompaniment Separation & Reverberation Removal, additionally), download models from [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) and place them in `tools/uvr5/uvr5_weights`.
+
+
+### Using Docker
+
+#### docker-compose.yaml configuration
+
+1. Environment Variables：
+  - is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation.
+
+2. Volumes Configuration，The application's root directory inside the container is set to /workspace. The default docker-compose.yaml lists some practical examples for uploading/downloading content.
+3. shm_size： The default available memory for Docker Desktop on Windows is too small, which can cause abnormal operations. Adjust according to your own situation.
+4. Under the deploy section, GPU-related settings should be adjusted cautiously according to your system and actual circumstances.
+
+
+#### Running with docker compose
+```
+docker compose -f "docker-compose.yaml" up -d
+```
+
+#### Running with docker command
+
+As above, modify the corresponding parameters based on your actual situation, then run the following command:
+```
+docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-DockerTest\output:/workspace/output --volume=G:\GPT-SoVITS-DockerTest\logs:/workspace/logs --volume=G:\GPT-SoVITS-DockerTest\SoVITS_weights:/workspace/SoVITS_weights --workdir=/workspace -p 9870:9870 -p 9871:9871 -p 9872:9872 -p 9873:9873 -p 9874:9874 --shm-size="16G" -d breakstring/gpt-sovits:dev-20240123.03
+```
+
+
+## Dataset Format
+
+The TTS annotation .list file format:
+
+```
+vocal_path|speaker_name|language|text
+```
+
+Language dictionary:
+
+- 'zh': Chinese
+- 'ja': Japanese
+- 'en': English
+
+Example:
+
+```
+D:\GPT-SoVITS\xxx/xxx.wav|xxx|en|I like playing Genshin.
+```
+## Todo List
+
+- [ ] **High Priority:**
+   - [ ] Localization in Japanese and English.
+   - [ ] User guide.
+   - [ ] Japanese and English dataset fine tune training.
+
+- [ ] **Features:**
+   - [ ] Zero-shot voice conversion (5s) / few-shot voice conversion (1min).
+   - [ ] TTS speaking speed control.
+   - [ ] Enhanced TTS emotion control.
+   - [ ] Experiment with changing SoVITS token inputs to probability distribution of vocabs.
+   - [ ] Improve English and Japanese text frontend.
+   - [ ] Develop tiny and larger-sized TTS models.
+   - [ ] Colab scripts.
+   - [ ] Try expand training dataset (2k hours -> 10k hours).
+   - [ ] better sovits base model (enhanced audio quality)
+   - [ ] model mix
+
+## Credits
+
+Special thanks to the following projects and contributors:
+
+- [ar-vits](https://github.com/innnky/ar-vits)
+- [SoundStorm](https://github.com/yangdongchao/SoundStorm/tree/master/soundstorm/s1/AR)
+- [vits](https://github.com/jaywalnut310/vits)
+- [TransferTTS](https://github.com/hcy71o/TransferTTS/blob/master/models.py#L556)
+- [Chinese Speech Pretrain](https://github.com/TencentGameMate/chinese_speech_pretrain)
+- [contentvec](https://github.com/auspicious3000/contentvec/)
+- [hifi-gan](https://github.com/jik876/hifi-gan)
+- [Chinese-Roberta-WWM-Ext-Large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large)
+- [fish-speech](https://github.com/fishaudio/fish-speech/blob/main/tools/llama/generate.py#L41)
+- [ultimatevocalremovergui](https://github.com/Anjok07/ultimatevocalremovergui)
+- [audio-slicer](https://github.com/openvpi/audio-slicer)
+- [SubFix](https://github.com/cronrpc/SubFix)
+- [FFmpeg](https://github.com/FFmpeg/FFmpeg)
+- [gradio](https://github.com/gradio-app/gradio)
+
+## Thanks to all contributors for their efforts
+<a href="https://github.com/RVC-Boss/GPT-SoVITS/graphs/contributors" target="_blank">
+  <img src="https://contrib.rocks/image?repo=RVC-Boss/GPT-SoVITS" />
+</a>

README.md

@@ -1,190 +1,3 @@
-<div align="center">
-
-<h1>GPT-SoVITS-WebUI</h1>
-A Powerful Few-shot Voice Conversion and Text-to-Speech WebUI.<br><br>
-
-[![madewithlove](https://img.shields.io/badge/made_with-%E2%9D%A4-red?style=for-the-badge&labelColor=orange
-)](https://github.com/RVC-Boss/GPT-SoVITS)
-
-<img src="https://counter.seku.su/cmoe?name=gptsovits&theme=r34" /><br>
-
-[![Licence](https://img.shields.io/badge/LICENSE-MIT-green.svg?style=for-the-badge)](https://github.com/RVC-Boss/GPT-SoVITS/blob/main/LICENSE)
-[![Huggingface](https://img.shields.io/badge/🤗%20-Spaces-yellow.svg?style=for-the-badge)](https://huggingface.co/lj1995/GPT-SoVITS/tree/main)
-
-
-[**English**](./README.md) | [**中文简体**](./docs/cn/README.md) | [**日本語**](./docs/ja/README.md)
-
-</div>
-
-------
-
-
-
-> Check out our [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw) here!
-
-https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb
-
-## Features:
-1. **Zero-shot TTS:** Input a 5-second vocal sample and experience instant text-to-speech conversion.
-
-2. **Few-shot TTS:** Fine-tune the model with just 1 minute of training data for improved voice similarity and realism.
-
-3. **Cross-lingual Support:** Inference in languages different from the training dataset, currently supporting English, Japanese, and Chinese.
-
-4. **WebUI Tools:** Integrated tools include voice accompaniment separation, automatic training set segmentation, Chinese ASR, and text labeling, assisting beginners in creating training datasets and GPT/SoVITS models.
-
-## Environment Preparation
-
-If you are a Windows user (tested with win>=10) you can install directly via the prezip. Just download the [prezip](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true), unzip it and double-click go-webui.bat to start GPT-SoVITS-WebUI.
-
-### Tested Environments
-
-- Python 3.9, PyTorch 2.0.1, CUDA 11
-- Python 3.10.13, PyTorch 2.1.2, CUDA 12.3
-
-_Note: numba==0.56.4 require py<3.11_
-
-### Quick Install with Conda
-
-```bash
-conda create -n GPTSoVits python=3.9
-conda activate GPTSoVits
-bash install.sh
-```
-### Install Manually
-
-#### Pip Packages
-
-```bash
-pip install torch numpy scipy tensorboard librosa==0.9.2 numba==0.56.4 pytorch-lightning gradio==3.14.0 ffmpeg-python onnxruntime tqdm cn2an pypinyin pyopenjtalk g2p_en chardet transformers jieba_fast
-```
-
-#### Additional Requirements
-
-If you need Chinese ASR (supported by FunASR), install:
-
-```bash
-pip install modelscope torchaudio sentencepiece funasr
-```
-
-#### FFmpeg
-
-##### Conda Users
-```bash
-conda install ffmpeg
-```
-
-##### Ubuntu/Debian Users
-
-```bash
-sudo apt install ffmpeg
-sudo apt install libsox-dev
-conda install -c conda-forge 'ffmpeg<7'
-```
-
-##### MacOS Users
-
-```bash
-brew install ffmpeg
-```
-
-##### Windows Users
-
-Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) and [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) in the GPT-SoVITS root.
-
-### Pretrained Models
-
-
-Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS/pretrained_models`.
-
-For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/damo_asr/models`.
-
-For UVR5 (Vocals/Accompaniment Separation & Reverberation Removal, additionally), download models from [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) and place them in `tools/uvr5/uvr5_weights`.
-
-
-### Using Docker
-
-#### docker-compose.yaml configuration
-
-1. Environment Variables：
-  - is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation.
-
-2. Volumes Configuration，The application's root directory inside the container is set to /workspace. The default docker-compose.yaml lists some practical examples for uploading/downloading content.
-3. shm_size： The default available memory for Docker Desktop on Windows is too small, which can cause abnormal operations. Adjust according to your own situation.
-4. Under the deploy section, GPU-related settings should be adjusted cautiously according to your system and actual circumstances.
-
-
-#### Running with docker compose
-```
-docker compose -f "docker-compose.yaml" up -d
-```
-
-#### Running with docker command
-
-As above, modify the corresponding parameters based on your actual situation, then run the following command:
-```
-docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-DockerTest\output:/workspace/output --volume=G:\GPT-SoVITS-DockerTest\logs:/workspace/logs --volume=G:\GPT-SoVITS-DockerTest\SoVITS_weights:/workspace/SoVITS_weights --workdir=/workspace -p 9870:9870 -p 9871:9871 -p 9872:9872 -p 9873:9873 -p 9874:9874 --shm-size="16G" -d breakstring/gpt-sovits:dev-20240123.03
-```
-
-
-## Dataset Format
-
-The TTS annotation .list file format:
-
-```
-vocal_path|speaker_name|language|text
-```
-
-Language dictionary:
-
-- 'zh': Chinese
-- 'ja': Japanese
-- 'en': English
-
-Example:
-
-```
-D:\GPT-SoVITS\xxx/xxx.wav|xxx|en|I like playing Genshin.
-```
-## Todo List
-
-- [ ] **High Priority:**
-   - [ ] Localization in Japanese and English.
-   - [ ] User guide.
-   - [ ] Japanese and English dataset fine tune training.
-
-- [ ] **Features:**
-   - [ ] Zero-shot voice conversion (5s) / few-shot voice conversion (1min).
-   - [ ] TTS speaking speed control.
-   - [ ] Enhanced TTS emotion control.
-   - [ ] Experiment with changing SoVITS token inputs to probability distribution of vocabs.
-   - [ ] Improve English and Japanese text frontend.
-   - [ ] Develop tiny and larger-sized TTS models.
-   - [ ] Colab scripts.
-   - [ ] Try expand training dataset (2k hours -> 10k hours).
-   - [ ] better sovits base model (enhanced audio quality)
-   - [ ] model mix
-
-## Credits
-
-Special thanks to the following projects and contributors:
-
-- [ar-vits](https://github.com/innnky/ar-vits)
-- [SoundStorm](https://github.com/yangdongchao/SoundStorm/tree/master/soundstorm/s1/AR)
-- [vits](https://github.com/jaywalnut310/vits)
-- [TransferTTS](https://github.com/hcy71o/TransferTTS/blob/master/models.py#L556)
-- [Chinese Speech Pretrain](https://github.com/TencentGameMate/chinese_speech_pretrain)
-- [contentvec](https://github.com/auspicious3000/contentvec/)
-- [hifi-gan](https://github.com/jik876/hifi-gan)
-- [Chinese-Roberta-WWM-Ext-Large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large)
-- [fish-speech](https://github.com/fishaudio/fish-speech/blob/main/tools/llama/generate.py#L41)
-- [ultimatevocalremovergui](https://github.com/Anjok07/ultimatevocalremovergui)
-- [audio-slicer](https://github.com/openvpi/audio-slicer)
-- [SubFix](https://github.com/cronrpc/SubFix)
-- [FFmpeg](https://github.com/FFmpeg/FFmpeg)
-- [gradio](https://github.com/gradio-app/gradio)
-
-## Thanks to all contributors for their efforts
-<a href="https://github.com/RVC-Boss/GPT-SoVITS/graphs/contributors" target="_blank">
-  <img src="https://contrib.rocks/image?repo=RVC-Boss/GPT-SoVITS" />
-</a>
+preload_from_hub:
+  - test
+  - mortimerme/sovits