Instructions to use ProbeX/Model-J__DINO__model_idx_0584 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_0584 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_0584") 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_0584") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0584", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68dc361d746b7b328068548336be43da8e155a34037d198edc05f945d057ee29
- Size of remote file:
- 5.37 kB
- SHA256:
- 6b83fb4b4a6d597850cbac41bfa426084a579d7408a0665b16a6b1fc80a7416b
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