Instructions to use ProbeX/Model-J__SupViT__model_idx_0902 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_0902 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_0902") 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_0902") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0902") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a21e5e717eab2dd7222052dca0356197289381f07474b3ceb96216c8dc621e62
- Size of remote file:
- 5.37 kB
- SHA256:
- c7d7fa579e5ccfe75bd92ba0f0e8e35e03b6f1bb19103fc3243695a613cc985f
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