Instructions to use ProbeX/Model-J__SupViT__model_idx_0697 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_0697 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_0697") 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_0697") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0697") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d62b89a653820960214058f88bc1c897191ebe6460bfa7388ddde702383962a7
- Size of remote file:
- 5.37 kB
- SHA256:
- bb6e90571f16a543dfa4c1b6471c23b52e8b5bdfb03d544c39dc994147387a7d
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