Instructions to use facebook/mms-1b-l1107 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-1b-l1107 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/mms-1b-l1107")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/mms-1b-l1107") model = AutoModelForCTC.from_pretrained("facebook/mms-1b-l1107") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 770e07a8899e1ac78917fb8b30559bc03562ccb259a3ed789cf2194cd7c689cb
- Size of remote file:
- 8.87 MB
- SHA256:
- 97fe8d47f9a8614c761b166ee384f905f532ccd23cce3fe479fcd44d74b761c8
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