Instructions to use ProbeX/Model-J__SupViT__model_idx_0951 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_0951 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_0951") 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_0951") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0951", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dec2cfd06897b542ebd5565d8f1613b20ab820d7fecf238f968fbb06fdef1cb6
- Size of remote file:
- 5.37 kB
- SHA256:
- 9ba113752aa91d7e1241834e76dd45248eac7663e2aa18c89a2cd6816df320fd
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