Instructions to use ProbeX/Model-J__DINO__model_idx_0788 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_0788 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_0788") 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_0788") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0788") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1b2a1fd6fc30293957b882c9e9e2016a0b88c2068f201ca264da0fbb46a45f0
- Size of remote file:
- 5.37 kB
- SHA256:
- 9f297d6bde0f88dcce1df87548fbcb4bdf14e76fe7baaebff4df4d811f6fdc9c
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