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:
- fb3c40335ce34638cc002f9aca3068ae2c676d9367aef8a1bb60b349f017020b
- Size of remote file:
- 8.93 MB
- SHA256:
- 5dd78c1d7d553c6e913a2a86bc268eee2712b037e283e0ca7a47405109700251
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