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:
- 84ae8c0edb58fefe282059a12f7d5929914ea4b218f56f712d593f0f49cef1be
- Size of remote file:
- 8.91 MB
- SHA256:
- 31f6b485556a95f58bbc6ca93bfd8d4f33828cae9b0aa7193ea670117dcf8d49
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