Instructions to use ProbeX/Model-J__SupViT__model_idx_0969 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_0969 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_0969") 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_0969") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0969", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80bd9170c6e5459ccd04d59bd0e0f561f9fb696ff67f79c7bacdcb273db09e10
- Size of remote file:
- 5.37 kB
- SHA256:
- 817383c56f0bda2a791df2b9b55d1efa1608ca9fbb9b9a93b1d0a3bf10a4f724
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