Instructions to use ProbeX/Model-J__DINO__model_idx_0039 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_0039 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_0039") 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_0039") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0039") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81b31883f16eeb3194f422a37e99ebba9f1c49567134a8bd1fccd62a03e55bb1
- Size of remote file:
- 5.37 kB
- SHA256:
- 842fcc6ac2b6f64c3fc0e68672167270ca807d53b8ca5c43d02c6eca3f9961e2
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