Instructions to use ProbeX/Model-J__SupViT__model_idx_0467 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_0467 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_0467") 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_0467") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0467", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f378e50863bea5cf1fddc0903b6f94fe90673bd53cc0adb3fbc2efda24fd8434
- Size of remote file:
- 5.37 kB
- SHA256:
- 087b5cf8465b71ea77f9ca1d62e74ed179f965def15a58709c174b5e26fadbb5
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