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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76156032dc2736e9775663290d59b181478b30c446870a632de05aea34fc0a5f
- Size of remote file:
- 8.91 MB
- SHA256:
- 6f40ed5f636446b836ccdb03bf2b0f01b9d995af1a91e2c2352aaf85fb05c19b
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