Instructions to use ProbeX/Model-J__SupViT__model_idx_0975 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_0975 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_0975") 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_0975") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0975") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 209522df481edbe81947442fd75c6e89def36be06dad8a2ad4b247a8282d088f
- Size of remote file:
- 5.37 kB
- SHA256:
- daf97f215eb7b79f4064d5426d0b313a36ac5fdbe19e440b4bc831898befab16
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