Instructions to use benjaminogbonna/demo_text_to_speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjaminogbonna/demo_text_to_speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="benjaminogbonna/demo_text_to_speech")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("benjaminogbonna/demo_text_to_speech") model = AutoModelForTextToSpectrogram.from_pretrained("benjaminogbonna/demo_text_to_speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74a96c99973937ae84399cc5c7335c8232415ea5f964aa084d066c50bcd3299d
- Size of remote file:
- 5.5 kB
- SHA256:
- ac5d9bcf265ad5d6a556fec463f9e5af738160b9f4b558116d201c4b317ac79a
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