Instructions to use ProbeX/Model-J__DINO__model_idx_0937 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0937 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0937") 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__DINO__model_idx_0937") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0937") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a02a361b85bf295069d12da1611af9e9a04ed24aad7134fdfe43c1c0a5263de2
- Size of remote file:
- 5.37 kB
- SHA256:
- b4c6b7814feb9c6522bf21f3806d65b87e9d3343cfd9064d4ecedddab7d8b59b
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