Instructions to use ProbeX/Model-J__SupViT__model_idx_0835 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_0835 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_0835") 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_0835") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0835", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9374148675d5d55e14c9cbdf3a78c1b0f7d255dab7ccbf68beefd11170b3987e
- Size of remote file:
- 5.37 kB
- SHA256:
- ebf19c09004cd0f819fb764d7f07cf6bb525c6f1041302c8fecb1763945d0652
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