Instructions to use ProbeX/Model-J__SupViT__model_idx_0213 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_0213 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_0213") 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_0213") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0213") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4a555b5b666f51b4e49492b4c7f215f099f6d92cf5a4ae32f701e702afe2017
- Size of remote file:
- 343 MB
- SHA256:
- 5ad8942c4e85b9c486731b2a0d52d6833c36e959d7e5acc8cd784145755c2f91
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