Instructions to use ProbeX/Model-J__DINO__model_idx_0065 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_0065 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_0065") 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_0065") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0065", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d83ff826e87f306c6f5804e5f5ebe3235de9375153bde4baa0f630d8de9653c
- Size of remote file:
- 343 MB
- SHA256:
- 6c7487dfe9f71af8b4404aa459f2487ad9d494e7b6ba1dc6fc403049bcacd39e
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