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:
- 3cb3187ba8373c58a5abb8bc2be8b7a5e754e8c043c8ca06e7f6c0af0bc706a8
- Size of remote file:
- 1.59 GB
- SHA256:
- c87d10d6a21b1a377432b3467aa75b9210c77a2ba4fa0f6562f8ce574ba222cc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.