Instructions to use superb/wav2vec2-large-superb-ic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superb/wav2vec2-large-superb-ic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="superb/wav2vec2-large-superb-ic")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("superb/wav2vec2-large-superb-ic") model = AutoModelForAudioClassification.from_pretrained("superb/wav2vec2-large-superb-ic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cad294fd28f332e020757b34f29b02d58c352e8a796aaaf70ceb380afa4d364
- Size of remote file:
- 1.26 GB
- SHA256:
- 90e162a5bf7c55f901d2a57d6d5bd172468cc2663e69444c76aa5496dcde1174
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