Instructions to use ProbeX/Model-J__DINO__model_idx_0167 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_0167 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_0167") 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_0167") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0167") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73d20c5b76b4e78f680385e05761df0d27eb7b98ee6aea4e0d8a2eee65caa284
- Size of remote file:
- 5.37 kB
- SHA256:
- 24d2ef917ff9967dbf75ef621c55076a4ada6a18dad8c4b3b57766c8f2856c6c
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