Instructions to use ProbeX/Model-J__SupViT__model_idx_0868 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_0868 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_0868") 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_0868") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0868") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45a65afbfab4494a95d7b66d5e9ccc0f0f4982cb151e06c742f2eb340665fa91
- Size of remote file:
- 5.37 kB
- SHA256:
- 6060f369a8c9c74d2f94ab062ca9e990157490ad6d80fd47d2dcb303d531ed5c
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