Instructions to use selinawisco/result_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selinawisco/result_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="selinawisco/result_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("selinawisco/result_2") model = AutoModelForAudioClassification.from_pretrained("selinawisco/result_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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