Instructions to use michael-chan-000/tts-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michael-chan-000/tts-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="michael-chan-000/tts-v2")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("michael-chan-000/tts-v2") model = AutoModelForTextToWaveform.from_pretrained("michael-chan-000/tts-v2") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- f68f7d8786ac9f9a9ff6c04843f198746763a984101452ed59257e9a8e86c240
- Size of remote file:
- 438 kB
- SHA256:
- 6260cd2e98235c9e181316db9fd6f716fbca1e314ef367ff338b988dcb54a76c
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