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:
- e8c0e8be27523e70e3cc1527480aefab2b5947c9754313571db67dde1f0ca8f4
- Size of remote file:
- 3.86 GB
- SHA256:
- 0f1d95ce43d27e03d5d8dd56c697c805460f967c793dd2cbec2e8e8012deda98
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