Instructions to use ProbeX/Model-J__SupViT__model_idx_0500 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_0500 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_0500") 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_0500") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10265f8dd72d720aae2bfff1852bd76a4ab42791115052f0c9da8091140b0936
- Size of remote file:
- 5.37 kB
- SHA256:
- 058db4c7864ff601ec5ad8a8eeb9c71177f061cefa0852356daf8e6a7d3a5cce
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