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:
- bed0fb5f717bbc1cd98bbc9d8f336902ce676af7ae64a6792fe21b31074fc06c
- Size of remote file:
- 8.86 MB
- SHA256:
- e7cb1862370c9108e93441203446359bce448fd3739abb8f81a0081ee2e62060
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