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:
- baea84b3facaaca5527ee2ba4f9a356e1852a9ec4f124df3a0ce453e1ec87a37
- Size of remote file:
- 8.89 MB
- SHA256:
- 75af4d97512bb8efa45372861faa410c7b7c77ca2c8fd2f82dd0eb4126dbdee6
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