Instructions to use ProbeX/Model-J__SupViT__model_idx_0375 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_0375 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_0375") 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_0375") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0375") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6369c52d6dfe15ec0fed5a769eb662b26ba0953ddc04250a562352ca4398a80f
- Size of remote file:
- 343 MB
- SHA256:
- aea4f33ed6275591159e437b3af149e4f81325e9b07c91da96ea76f6553b4b5d
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