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:
- 6e20d7a8f88b685fcda76a33131d03ab250ad6610c2dab1fcc8c1b0c600ce245
- Size of remote file:
- 838 kB
- SHA256:
- 63bc6a63f3e3217ff05b5e5e0adb8ce89cdbb9da086e74d0c469c6465e611221
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