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:
- ee557a24f1f86a465f3c32f286d1c7deb53304827c048f67fdcf64bbb35f6b93
- Size of remote file:
- 8.92 MB
- SHA256:
- a78c672a4742400f7c00deb9c307fc0343628b7a70220ddd6314cd0f80812695
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