Instructions to use ProbeX/Model-J__SupViT__model_idx_0536 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_0536 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_0536") 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_0536") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0536", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70f338b4afd7df0dde518735b27fe3e80f1f00e11bf50a784cf1492525467c86
- Size of remote file:
- 5.37 kB
- SHA256:
- c302b2b78bc850f90585b964f24726b8a7ad9db06e6d591da68055cb6279cb4a
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