Instructions to use ProbeX/Model-J__SupViT__model_idx_0235 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_0235 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_0235") 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_0235") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0235", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80efe393ee19e7d5edbb9a0072fe516690bef2184f5a43de508256e2ac6fe70d
- Size of remote file:
- 5.37 kB
- SHA256:
- e717e2f2d05f3e8c87a425a6f84752859931b4a5dcd17b778527704363ad4983
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