Instructions to use ProbeX/Model-J__DINO__model_idx_0805 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_0805 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_0805") 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_0805") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0805", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa385e4cbd4c203b5d08c6692af8b7cc9703e2c2191f04a07a0795ec3189952a
- Size of remote file:
- 5.37 kB
- SHA256:
- 5dc40cfcefe8c11474e293e5869768f0f58d9c0e736b83568ff470d5952af4c8
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