Instructions to use ProbeX/Model-J__DINO__model_idx_0286 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_0286 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_0286") 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_0286") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0286", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd77c57034a4b23e5208fac2353f83e40705e62fae08d8834e75e8d3fc27656b
- Size of remote file:
- 5.37 kB
- SHA256:
- 79240ff62e1c8478c3e0e02c8fe1e899766685a5f03956ccf381afd2c9d99f04
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