Instructions to use ProbeX/Model-J__SupViT__model_idx_0475 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_0475 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_0475") 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_0475") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0475") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d13ea74eb262e197bb5ba0a7f09d0b8db2cd41f638b8b06b40292a9081151612
- Size of remote file:
- 5.37 kB
- SHA256:
- 66f7b94195dd300f4ce7fe7ac01225a3936cab1031f2c90a58180f705f4b1aa6
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