Instructions to use ProbeX/Model-J__SupViT__model_idx_0928 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_0928 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_0928") 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_0928") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0928") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba58b81f9de2564199381d4c283ef64d01dab24f52df32f3f34cb25661aa91a7
- Size of remote file:
- 5.37 kB
- SHA256:
- c14448ec9704cbb6e5cc5d1698cafc340d3c777563f4710710d7f42d937bff18
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