Instructions to use facebook/mms-lid-2048 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-lid-2048 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="facebook/mms-lid-2048")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("facebook/mms-lid-2048") model = AutoModelForAudioClassification.from_pretrained("facebook/mms-lid-2048") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9a1bfbf37a018656c921c113bfcd15d6ce219fb73e29d0fced75b307d1b28a1
- Size of remote file:
- 3.87 GB
- SHA256:
- 87ce12fd5c2e86d1bdeedb26b651f9367091a5d64962c5806f0ff767e79ad971
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