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:
- a892d6dfb434c5cf9ca2505910d1044ff5b1f872ad049b35439cef440734f5e7
- Size of remote file:
- 567 MB
- SHA256:
- cdc44fee3c62b5743913e3147ed75f4e8ecfb52dd7a0f0f7387094b406ff0ee6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.