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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db8be05322e2b167060932938d7eda01b590c0c470558e5f81d0b5a55aa028a0
- Size of remote file:
- 8.95 MB
- SHA256:
- f1dbfddb2329a93a08db233de6095cfdb0de98642645cc98341795b9b600d010
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