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 tokenizer.json from drbaph/s2-pro-fp8: direct link, hf CLI and curl.
- Browser
- Download file 12.2 MB
-
https://huggingface.co/drbaph/s2-pro-fp8/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://drbaph/s2-pro-fp8@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/drbaph/s2-pro-fp8/resolve/refs%2Fpr%2F1/tokenizer.json
12.2 MB
- Xet hash:
- ab939bfbfdde24485101aa13a1a2e24c0e3b726c521815739e99780b5d0942c3
- Size of remote file:
- 12.2 MB
- SHA256:
- f24e08099d45a8adf3f52f5f0b03276e433bb9d689bb15fcbcc48ce58744588b
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