Instructions to use ProbeX/Model-J__SupViT__model_idx_0523 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_0523 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_0523") 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_0523") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0523", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15e3d9349ab3bc1f368f789c4e10da8e465638dc9244bed9152365597494e102
- Size of remote file:
- 5.37 kB
- SHA256:
- bf5780ac0401f71fe7dbc9fafec326c318a697120f2493daefcce5425a6475b9
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