Instructions to use ProbeX/Model-J__SupViT__model_idx_0607 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_0607 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_0607") 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_0607") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0607") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba311e890df9896586c9fa55d8559c1e39ba7e8899ab8ea49b0af3965780103d
- Size of remote file:
- 343 MB
- SHA256:
- be6b6ab37c4f72794391db4cfcabbde2251ddec0f9b6b49c58bd30137ed1d286
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