Instructions to use ProbeX/Model-J__SupViT__model_idx_0170 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_0170 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_0170") 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_0170") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0170") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2612aaadb1ea3a23a3a37526052aa8b3b3ccd0a95aa6f32975f19f38feb7bf90
- Size of remote file:
- 5.37 kB
- SHA256:
- 4f75ee656461774be0085fb0bf218438446bc4602d2d94267c4fa5afd6c3a107
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