Instructions to use ProbeX/Model-J__SupViT__model_idx_0841 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_0841 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_0841") 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_0841") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0841", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2446e92b388f15bd2430e20ce0f7489778af3676fe664586865f1549dc6cb08f
- Size of remote file:
- 5.37 kB
- SHA256:
- 31fe103bae892b8d27ae1598ef23404e0494bdb5d0a66e7bfd4be08f205b8851
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