Instructions to use ProbeX/Model-J__DINO__model_idx_0060 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_0060 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_0060") 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_0060") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0060", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 713a5a2284d765aa5f2768c0152bcd783927673fa675569b7447ae9f6eb48d85
- Size of remote file:
- 5.37 kB
- SHA256:
- 2eafc722a6fd57913af0982afe04c251458c300b5401796cec5b59114cda1cb3
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