Instructions to use ProbeX/Model-J__SupViT__model_idx_0064 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_0064 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_0064") 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_0064") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0064") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8ec7773cac1afff811e68f00dc152930d7ea4628488f03b35571d020a9f22a1
- Size of remote file:
- 5.37 kB
- SHA256:
- 90db1840314117095dfb8af8b6bc7cd0c0700eb618586fda45c80a96eb5004e0
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