Instructions to use ProbeX/Model-J__SupViT__model_idx_0415 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_0415 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_0415") 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_0415") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0415") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4071c0ee26ef05db0b1f572bc95b1ed26bb4139900bf60041de8ddfffd5d6e8
- Size of remote file:
- 5.37 kB
- SHA256:
- c0530198d2140cd25da531cb8b0075793a1f15fb5b83505f165f7a1a7eb14bdb
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