Instructions to use ProbeX/Model-J__SupViT__model_idx_0761 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_0761 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_0761") 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_0761") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0761") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 915261b9c0802dc7923bd7727e009a28ac39009f5c0ec0afa9b6d112c103e800
- Size of remote file:
- 5.37 kB
- SHA256:
- a5d98a8b340fea365d189196daab284740d09a9b8e36aa0741f35706cf2bb08b
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