Instructions to use ProbeX/Model-J__DINO__model_idx_0566 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_0566 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_0566") 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_0566") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0566", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ac399ebe97cd5ace8f789eed42bdf05fa4233c5e51025911c81f91ee959f395
- Size of remote file:
- 343 MB
- SHA256:
- 8b5aa808711c2984ed33e3afe2de257723e30e0c43002ab3eae70f010f349ed9
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