Instructions to use ProbeX/Model-J__SupViT__model_idx_0571 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_0571 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_0571") 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_0571") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0571") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d7d17d56730b79e98349426c5d9bb462d96c51d6426a0c20fd105b10c4d6021
- Size of remote file:
- 5.37 kB
- SHA256:
- 6bd2ef210dfe99089eb279b9ab9ea29832a6dc02ccb0e5c0f41ec02b8ddfb287
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