Instructions to use anton-l/wav2vec2-base-superb-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/wav2vec2-base-superb-sv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/wav2vec2-base-superb-sv")# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-base-superb-sv") model = AutoModelForAudioXVector.from_pretrained("anton-l/wav2vec2-base-superb-sv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 092c831aecd73e5b2f7f7bf2f15189955e330fdb067cc234d59d96148f078f3e
- Size of remote file:
- 404 MB
- SHA256:
- dca2df146a2340fa99af66baee448b42560e73f2e4f10dc507eb5982987e0f7a
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