Instructions to use ProbeX/Model-J__SupViT__model_idx_0752 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_0752 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_0752") 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_0752") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0752") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8464b0b10f04a7204b8c12a8405fb6532b61a31b35cbfa7dd1bd3aac17e720b
- Size of remote file:
- 343 MB
- SHA256:
- eec0d5a56bd9e9db8878cdf9250c84cdf1705380f24d75782d0399a97c0bdff4
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