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:
- 905b77a7cc4063b27c19651cb95c2ddf7039c89d8fb36aee5827f7e31427108e
- Size of remote file:
- 8.95 MB
- SHA256:
- 2b97630dd09be24dbf9d195a803a730ef60faebf0d51222563b2c26cccf7b4b2
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