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:
- 2fa4d8a58ddd291bc4614c455ac6d19cd4e0599ec057cf5766f139974d7cb8f9
- Size of remote file:
- 8.92 MB
- SHA256:
- 56f9873dea9f50520ed0eb55f8b8333e98ec5dcc5323a6ba42da3e92439f82f6
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