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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ac9447e515276a8ed727dc0d5a8e047ffdd9d8b744a2b64305f07f08711dd8b
- Size of remote file:
- 8.92 MB
- SHA256:
- 734a4ac8fe8a1865e5a2b8d02e80a36095e7eadb328e3819f7c560b0c5b8ad9a
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