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:
- 13b1bea62adb37811b28a8696df58654d2235b22f334a501c1afbc9c009c5b38
- Size of remote file:
- 17.2 MB
- SHA256:
- 1a222563314bf6ffe3471622bff017ff5bb0630f2924faf44216195ebfef2af3
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