Instructions to use ProbeX/Model-J__DINO__model_idx_0297 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_0297 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_0297") 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_0297") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0297") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5060b1b4d12e4f1db2560fc30ea62e6500d94abe6a659a05428dea3787181585
- Size of remote file:
- 5.37 kB
- SHA256:
- 75dbdac2be0c0b44182d64e1d1ead4f28a1d411b189c48078357048b351c8a2e
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