Instructions to use ProbeX/Model-J__SupViT__model_idx_0636 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_0636 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_0636") 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_0636") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0636", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9abed58cde44ec10f634c2526ee9d1745978c5cdaa5693744e6d2698778c73f
- Size of remote file:
- 5.37 kB
- SHA256:
- a550d17422f1e8af33f0a0c1718e733d16031cda8aceedfe3c16a0cd4879e03b
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