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:
- 44ba6a6b46d1e23d5b45bce0fee792831ab4590b20b3a0c92e41fca923e2651b
- Size of remote file:
- 8.96 MB
- SHA256:
- 4077dee9e5f4f5ec59b6a23f95762924c71ddde14253d3430f21338188e5538b
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