Instructions to use ProbeX/Model-J__DINO__model_idx_0240 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_0240 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_0240") 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_0240") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0240", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d786d0e400ea5dd6451d407995c7275f1909553113f304d173f4a3f5cc5ceb4
- Size of remote file:
- 5.37 kB
- SHA256:
- 44fa5d4c00b17255bffa71decdcc1a41be5c8be65a54df90f8985ff2dfba34a5
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