Instructions to use ProbeX/Model-J__SupViT__model_idx_0742 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_0742 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_0742") 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_0742") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0742") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2807da640b71817adda75cb2fff3b6e52393d7d68dd8cf2db4b86e73f37046b8
- Size of remote file:
- 5.37 kB
- SHA256:
- 4dc6307ec1c5932d5ee89737100ce269ee7ca45813b8af5fb10995a047a08789
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