Instructions to use ProbeX/Model-J__SupViT__model_idx_0412 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0412 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0412") 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("ProbeX/Model-J__SupViT__model_idx_0412") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0412") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7eff8bd4660ac7abbc786f838a2daa742514ac90e86c2c7ba1e43d40a2f98477
- Size of remote file:
- 5.37 kB
- SHA256:
- 59f7f5849e7cc7285812edc1d3a91ca032dd5924d501b9cb5c91707adc04d0a4
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