Instructions to use ProbeX/Model-J__SupViT__model_idx_0314 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_0314 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_0314") 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_0314") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0314", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f7997b74dd61104f057628b16f29a59c1807631698ac9b8aad493a43a604619
- Size of remote file:
- 5.37 kB
- SHA256:
- ec0234402ef8e92d02a1b589c20711f75c037aef5d9987c95948a0bd097eba9a
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