Instructions to use KaushalB/ViTForMusicClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KaushalB/ViTForMusicClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="KaushalB/ViTForMusicClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("KaushalB/ViTForMusicClassification") model = AutoModelForImageClassification.from_pretrained("KaushalB/ViTForMusicClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2a4dcb4e03daf0eff5de23f4a15b914dced4cfef2f85ddc6b7676582c87825b
- Size of remote file:
- 700 MB
- SHA256:
- a0ea76f7d71a48349ddcc05f83ddbf8f8f117f78a49c05dd6c38d1e6db47a9d1
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