Instructions to use Wfloat/wfloat-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Piper
How to use Wfloat/wfloat-tts with Piper:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 484 Bytes
f71bc95 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from wfloat_tts import load_generator, write_wave
def main() -> None:
generator = load_generator(
checkpoint_path="model.safetensors",
config_path="config.json",
)
audio = generator.generate(
text="Hey there, how are you today?",
sid=11,
emotion="neutral",
intensity=0.5,
)
out_path = "out.wav"
write_wave(out_path, audio.samples, audio.sample_rate)
print(out_path)
if __name__ == "__main__":
main()
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