Instructions to use scarxity/fish-speech-s2-pro-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scarxity/fish-speech-s2-pro-nf4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="scarxity/fish-speech-s2-pro-nf4")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("scarxity/fish-speech-s2-pro-nf4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download codec.pth from scarxity/fish-speech-s2-pro-nf4: direct link, hf CLI and curl.
- Browser
- Download file 1.87 GB
-
https://huggingface.co/scarxity/fish-speech-s2-pro-nf4/resolve/main/codec.pth
- Command line
-
hf download hf://scarxity/fish-speech-s2-pro-nf4/codec.pth
-
curl -L -o codec.pth https://huggingface.co/scarxity/fish-speech-s2-pro-nf4/resolve/main/codec.pth
1.87 GB
- Xet hash:
- 708d4c6aba8134c5fb74878b268f89f0df22f72ff1a38e0db89a159e85d4ab0f
- Size of remote file:
- 1.87 GB
- SHA256:
- 74fc41c5a7151c6f350af8bd7e5d6e3accfcc7f3dfbfac23afd35af07052bb2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.