Instructions to use ProbeX/Model-J__DINO__model_idx_0282 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_0282 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_0282") 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_0282") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0282") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2644d9a98828960be5297493d791c5125615e59461316d232338efdced38bad3
- Size of remote file:
- 5.37 kB
- SHA256:
- 1edc729b63eb011561801d83095a1e947b5ba7d95622bd5368257d10c8fac010
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