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:
- e15fdee6bc93d6c70dae69349ed0d39b2d0234f7b6bd9c4ea044da773bbc0da0
- Size of remote file:
- 8.92 MB
- SHA256:
- da8c8b23697759f91f03a79670ecf211e3717a0e4dcad524def326028dd71aac
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