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:
- 5db8b1b884465c49eb109275919003faf07d1df2b1b9d90fcecbbe9709dc2df5
- Size of remote file:
- 8.84 MB
- SHA256:
- 6b18639b92d2338e4536e3d01a8c3a0cdc2db3506c897b1cd8f7e0793119cd1a
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