Instructions to use ProbeX/Model-J__SupViT__model_idx_0408 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_0408 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_0408", device_map="auto") 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_0408") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0408", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5eb7b2a81538c96bd26e7b357c1882db3b55e7bbfe7a10b4fd019fcb8ea67af
- Size of remote file:
- 5.37 kB
- SHA256:
- 8debb1fee4310934ea86f2301ea78e46abc57cb24f768a679a372293767de4b4
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