Instructions to use ilyes25/MMS_10langs_simultane with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilyes25/MMS_10langs_simultane with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ilyes25/MMS_10langs_simultane")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ilyes25/MMS_10langs_simultane") model = AutoModelForCTC.from_pretrained("ilyes25/MMS_10langs_simultane") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31ce2bb2001953a07fac7a050a05a611fbf915d78484a865932387dc223beff1
- Size of remote file:
- 5.37 kB
- SHA256:
- 13d53832804f880bc5c2101291442e738d9d5b9a6e6bc7155d0fb61bcbb4c577
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