Instructions to use ProbeX/Model-J__SupViT__model_idx_0743 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_0743 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_0743") 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_0743") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0743", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f7d8bd9b121e560ebece83782962cc0f58f25d20f485e6c665b9b55c8526bbb
- Size of remote file:
- 5.37 kB
- SHA256:
- 79f2329f42d8ca7a5735332dbb50716c9527497872efd6032c91b832c933e3e8
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