Instructions to use ProbeX/Model-J__SupViT__model_idx_0446 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_0446 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_0446") 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_0446") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0446") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 506cb7e5533d08eae60e129ff35a9f8db97cc22989b43ff72d9916edf638cf23
- Size of remote file:
- 5.37 kB
- SHA256:
- 1fc9b6d7d97b57db14263c6dcb77be840bbec8301a85355478078decf3432c5b
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