Instructions to use facebook/mms-lid-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-lid-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="facebook/mms-lid-256")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("facebook/mms-lid-256") model = AutoModelForAudioClassification.from_pretrained("facebook/mms-lid-256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65b01cdb1c672390c5e47424cefc230c977daed47eab5d940ce8af5ee26d0400
- Size of remote file:
- 3.87 GB
- SHA256:
- 258e7f82f96c791bf45ca0caaddd0f8d26254443c0a403779824820aebe56b87
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