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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ac2aba41927b842ca013489cb2c622c2002f47844fcc5a12ed0e536941a418a
- Size of remote file:
- 5.5 kB
- SHA256:
- 78afc2c19b3499a630b65d105c3d24f0615aada1ab518033a503cd310415bb14
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