Instructions to use eustlb/higgs-v2-archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eustlb/higgs-v2-archive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="eustlb/higgs-v2-archive")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("eustlb/higgs-v2-archive") model = AutoModelForTextToWaveform.from_pretrained("eustlb/higgs-v2-archive") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d68446dc12c14e7b1eae0839e26c03cb8d76827a6225364a0c1914f0bff904bc
- Size of remote file:
- 4.93 GB
- SHA256:
- a7918bd0a6b383d907b0a6083c825dc967bb24ff8485dbdeffeb214ed4e61cef
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