Instructions to use facebook/mms-1b-l1107 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-1b-l1107 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/mms-1b-l1107")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/mms-1b-l1107") model = AutoModelForCTC.from_pretrained("facebook/mms-1b-l1107", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac9d2e41c4c563e7ee9e13609cc8fc016d3621392cd8bd10778597bdeca93f66
- Size of remote file:
- 8.89 MB
- SHA256:
- 71c2d9d8ef4691f52f3647b5e47c58c2531ba55a8201aed4e3b47a70f1143d5d
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