Instructions to use ProbeX/Model-J__SupViT__model_idx_0411 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_0411 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_0411") 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_0411") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0411") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a28e499108f1155f16ae137ca919cbacb5ec4e0b9b1256ff8808c73c4fdf7555
- Size of remote file:
- 5.37 kB
- SHA256:
- ebc03d0726ed15d7a75ff0e1aed7052e68b7d85ef6008c950e3306c71f9699ca
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