Instructions to use wetdog/speecht5_tts_commonvoice_ca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wetdog/speecht5_tts_commonvoice_ca with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="wetdog/speecht5_tts_commonvoice_ca")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("wetdog/speecht5_tts_commonvoice_ca") model = AutoModelForTextToSpectrogram.from_pretrained("wetdog/speecht5_tts_commonvoice_ca") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 763c75ecc78910f81e1f880370d191505b23a210e8072c2530f837db3c1310be
- Size of remote file:
- 585 MB
- SHA256:
- 905f5bef4ef017cd06396933ce44207e51ab12deda31760aed83828736708025
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