Instructions to use ProbeX/Model-J__SupViT__model_idx_0796 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_0796 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_0796") 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_0796") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0796", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e56ebfc4e144006a176900076c9e7a94536c5b2690227ceb5afb19df72bfcae
- Size of remote file:
- 5.37 kB
- SHA256:
- a80602040fbd5d4035f188f8b32bf008005bfc00abe85f5b3b58a599b82c3231
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