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:
- c225aae3268a98b085eeee929f46a1d9b6c0f47c84b9c1c850540c223c569e43
- Size of remote file:
- 8.86 MB
- SHA256:
- 7d7585e13c9cba420b0de8bd67e8322e410fc8f913ea03c881c0b865f16b10b7
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