Instructions to use ProbeX/Model-J__SupViT__model_idx_0440 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_0440 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_0440") 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_0440") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0440") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecd16b1ad492e610aeb5347b72cbe84e21cc38361273e77b10b7e4a603f2bc07
- Size of remote file:
- 5.37 kB
- SHA256:
- 5f0bd857f2ba3fdb1a6b2df957be5b34bac20a2acd30b62a2cc3fb98d8178fff
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