Instructions to use Chithekitale/PhD_tts_updated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chithekitale/PhD_tts_updated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Chithekitale/PhD_tts_updated")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Chithekitale/PhD_tts_updated") model = AutoModelForTextToSpectrogram.from_pretrained("Chithekitale/PhD_tts_updated") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d658f5c0bcf2de06ffb431cbc1db8c8cf29090c1ac097280f7e34f3f69789758
- Size of remote file:
- 578 MB
- SHA256:
- e073b62e4ddd00501fa93d0cf110edb0210388ed454539bdbb1bb1a064ea01a2
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