Instructions to use ProbeX/Model-J__SupViT__model_idx_0606 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_0606 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_0606") 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_0606") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0606", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8f5fefdb464293b05812803fe201ebb7542bd641e100c9496f642d56f0f07d3
- Size of remote file:
- 5.37 kB
- SHA256:
- 8048839fa48fac5c6798c2a40933261710e32f03cfaea136b1511a8f6a0c32aa
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