Instructions to use ProbeX/Model-J__DINO__model_idx_0750 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_0750 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_0750") 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_0750") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0750", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80a6fc662504b8162c88de0eb1da0e872927b9ad8590d7ce470b772582531656
- Size of remote file:
- 5.37 kB
- SHA256:
- 1bb9c6d41b7c9b121287530d57755817b2993df294d5334a0985fb7bcdffa510
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