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:
- 01181bcaeb513fa90b90fe003ad274dbce3cad811d2f5a3d4d27b2d53d505b91
- Size of remote file:
- 4.97 GB
- SHA256:
- a8c7462c593a3d710d4de2fcd3ee6fc5f35a520e006553659ba3123de51c0a8d
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