Instructions to use arunps/wav2vec2-base-adsids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arunps/wav2vec2-base-adsids with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="arunps/wav2vec2-base-adsids")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("arunps/wav2vec2-base-adsids") model = AutoModelForAudioClassification.from_pretrained("arunps/wav2vec2-base-adsids", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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docs: add complete Hugging Face model card for wav2vec2-base-adsids with dataset details, usage examples, and updated performance metrics
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