Instructions to use ProbeX/Model-J__SupViT__model_idx_0041 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_0041 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_0041") 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_0041") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0041", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0a7378ef097b001d42e176b29e5eed9a664ab967f9ccc123c554d054828ca07
- Size of remote file:
- 5.37 kB
- SHA256:
- 8b389bd82f6b6613a539367954318a8acf107b5db95c8147c250a019bbe7f4bb
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