Instructions to use lithish2602/sample_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lithish2602/sample_data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="lithish2602/sample_data")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("lithish2602/sample_data") model = AutoModelForTextToSpectrogram.from_pretrained("lithish2602/sample_data") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 430c3d2475eefd5c1c156ea083da6de16b4b1e380e0208ba84ccb241360d1044
- Size of remote file:
- 5.43 kB
- SHA256:
- 0a07297637dcfcbb27d215e8237e29698629016064606149fb94501e13fefdfe
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