Instructions to use ProbeX/Model-J__SupViT__model_idx_0124 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_0124 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_0124") 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_0124") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0124", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- def343302429628efecd6ec0263addf519b8198de125c3a287d2fc59fbaab247
- Size of remote file:
- 5.37 kB
- SHA256:
- 9389fce1875ba5b7153583e61ffcab1e68a224dc31893f23aed9f4f93cc4c371
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