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:
- 8bcc427229d99e369c53c8de836bb039dbfbdbc5acb292773c846c870c9bd690
- Size of remote file:
- 8.86 MB
- SHA256:
- a1b9b48ce43dd26c54b785eb86941c4ae7a92fe93cfa04d2fcd446701cf29de1
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