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:
- 690d5de940f6874f6d907e569deb9194f9740e2d1133bdf4bb653cad327cda59
- Size of remote file:
- 8.9 MB
- SHA256:
- 909594d84e77329bf06984473f415945c26226d07025f8852f8e19684a782295
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