Instructions to use osllmai-community/whisper.cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osllmai-community/whisper.cpp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("osllmai-community/whisper.cpp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 971539eabfa951d62cc5e06672e676da1e5e8768115056362fe6301b664b4ea4
- Size of remote file:
- 874 MB
- SHA256:
- 317eb69c11673c9de1e1f0d459b253999804ec71ac4c23c17ecf5fbe24e259a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.