Instructions to use ProbeX/Model-J__SupViT__model_idx_0331 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_0331 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_0331") 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_0331") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0331", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d8920ac211f1af59465383915e8a5912b2f9a0708c72106225d9cd57a67277b
- Size of remote file:
- 5.37 kB
- SHA256:
- a19fa7de2c04a1138c5104f8e8c779b7a098c5493479f6b29bceac4a5e5a28c8
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