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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download state.db from KaushalB/ViTForMusicClassification: direct link, hf CLI and curl.
- Browser
- Download file 350 MB
-
https://huggingface.co/KaushalB/ViTForMusicClassification/resolve/main/state.db
- Command line
-
hf download hf://KaushalB/ViTForMusicClassification/state.db
-
curl -L -o state.db https://huggingface.co/KaushalB/ViTForMusicClassification/resolve/main/state.db
350 MB
- Xet hash:
- 0cc3bfcee9f0d3183a16eec648082a3bd7ae257359364617bc7a930457670e94
- Size of remote file:
- 350 MB
- SHA256:
- cd10d354f3aa4aec0dae3940ee299145d3d33a6cd74f1f01704018e2903f2f3b
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