Instructions to use ProbeX/Model-J__DINO__model_idx_0163 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_0163 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_0163") 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_0163") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0163") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d117144d9a18754f8e48754a0a5d30f9b2234b315c40f7b473c554ce7aea395
- Size of remote file:
- 5.37 kB
- SHA256:
- 4a66e42df7dee4a049f5971540c48c0f4487d7572fdf9e4132cb8216cbdb8c11
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