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:
- fd70e2ab36a9058f1ac328cab62a006ab963da907b230208780c6c7d20f29bd9
- Size of remote file:
- 1.59 GB
- SHA256:
- 02a36e0c47281184ecbee3b9329fc4546a57674d9faca89cb2d3110c4c6bb56b
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