Instructions to use ProbeX/Model-J__SupViT__model_idx_0013 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_0013 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_0013") 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_0013") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0013") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72c5cd44c3e1725786c00dc7848990b3a1aaea56ab2f49f5293eac7da7e6cfb9
- Size of remote file:
- 5.37 kB
- SHA256:
- 940bbe9fb35f907754afd5ae77c07bbe85b66bbb58319dd56a965e49366f4463
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