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:
- 0d57184d34ae7d736e5bb2db5bf83debe730bd53dcefa235a0979b9dcfd33fb3
- Size of remote file:
- 488 MB
- SHA256:
- c6138d6d58ecc8322097e0f987c32f1be8bb0a18532a3f88f734d1bbf9c41e5d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.