Instructions to use facebook/mms-1b-fl102 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-1b-fl102 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/mms-1b-fl102")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/mms-1b-fl102") model = AutoModelForCTC.from_pretrained("facebook/mms-1b-fl102") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d61127bef370cdf7ff71a23497d344e693d9dd15a3aca6e2d2d970baf16626af
- Size of remote file:
- 9.08 MB
- SHA256:
- 86ad9819d21d89589807fe44752afb69d6705dbe7c38404ba1bf114895d0911f
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