Instructions to use ProbeX/Model-J__SupViT__model_idx_0473 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_0473 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_0473") 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_0473") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0473", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7478f065baf9b7b091549fd8a3f78defd40700b8c0c7bad8e503dd7e33731845
- Size of remote file:
- 5.37 kB
- SHA256:
- 2e1aa54cb19f5e6359b9c62e1732146b04cda78591b00e181ed178555c9ff94a
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