Instructions to use ProbeX/Model-J__SupViT__model_idx_0225 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_0225 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_0225") 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_0225") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0225", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d0b0c3c22ffdec44e7434647df54c0d668c0f4c961c5cf5e2b3fc23a9da31f7
- Size of remote file:
- 5.37 kB
- SHA256:
- 8af9e2a46af5c6dce1b63554e6ce8910017e1fadb6ef8e7e4dc33d43207d9463
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