Instructions to use facebook/mms-1b-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-1b-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/mms-1b-all")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/mms-1b-all") model = AutoModelForCTC.from_pretrained("facebook/mms-1b-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c7c56dc0dabdb5c2589a4838ef514b52b6951b1aebf4463ba3fc6a86c221547
- Size of remote file:
- 8.86 MB
- SHA256:
- 9e54c514dc8746e9c0c363334c241df4ac73e1b01386f3ed90f676323e1a11c6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.