Instructions to use gitgato/mabam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gitgato/mabam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="gitgato/mabam")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("gitgato/mabam") model = AutoModelForTextToSpectrogram.from_pretrained("gitgato/mabam") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5d686c572279d9c5346aee68f95a446e2a7e5d4dc42e8ac72b18a8223f32b0d
- Size of remote file:
- 5.05 kB
- SHA256:
- 2348a7d121ebb0f003e5327a860d2b586573a1dfa4f4efd4966d03b80bdffb6b
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