Instructions to use midoiv/Audio_Class_CREMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midoiv/Audio_Class_CREMA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="midoiv/Audio_Class_CREMA")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("midoiv/Audio_Class_CREMA") model = AutoModelForAudioClassification.from_pretrained("midoiv/Audio_Class_CREMA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from midoiv/Audio_Class_CREMA: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
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https://huggingface.co/midoiv/Audio_Class_CREMA/resolve/main/.gitignore
- Command line
-
hf download hf://midoiv/Audio_Class_CREMA/.gitignore
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curl -L -o .gitignore https://huggingface.co/midoiv/Audio_Class_CREMA/resolve/main/.gitignore
13 Bytes
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