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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60f77f8189eca131925ed4cc8f6eddade3b01a9b51d4cdeadda0de5ec612dbe4
- Size of remote file:
- 8.92 MB
- SHA256:
- 41826c7eb0663f852b7dfd6161fef33e087954e34afa28f43fe167192ab05b84
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