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:
- bca16e4561bc0467d400ea8afbfb3ffae841dcd26b2f8729f07c73ee2ec6ac62
- Size of remote file:
- 8.89 MB
- SHA256:
- 36968095a44fa91c26eb2808fcf368cb678a3b87cae1c463502e8949d8be0012
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