Text-to-Speech
Transformers
Safetensors
fish_qwen3_omni
instruction-following
multilingual
quantized
fp8
comfyui
comfy
multi-turn
multi-speaker
sglang
Instructions to use drbaph/s2-pro-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drbaph/s2-pro-fp8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="drbaph/s2-pro-fp8")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("drbaph/s2-pro-fp8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download codec.pth from drbaph/s2-pro-fp8: direct link, hf CLI and curl.
- Browser
- Download file 1.87 GB
-
https://huggingface.co/drbaph/s2-pro-fp8/resolve/refs%2Fpr%2F1/codec.pth
- Command line
-
hf download hf://drbaph/s2-pro-fp8@refs/pr/1/codec.pth
-
curl -L -o codec.pth https://huggingface.co/drbaph/s2-pro-fp8/resolve/refs%2Fpr%2F1/codec.pth
1.87 GB
- Xet hash:
- 708d4c6aba8134c5fb74878b268f89f0df22f72ff1a38e0db89a159e85d4ab0f
- Size of remote file:
- 1.87 GB
- SHA256:
- 74fc41c5a7151c6f350af8bd7e5d6e3accfcc7f3dfbfac23afd35af07052bb2f
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