Instructions to use ProbeX/Model-J__DINO__model_idx_0198 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_0198 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_0198") 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_0198") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0198", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8acb1f0b626a26c28fe9eb6f29f0c379066a61737cbe50db4eabbe3e5137eb1e
- Size of remote file:
- 5.37 kB
- SHA256:
- 86cc0e2f6976cff139b80d3bfbdef92931fe28d894486713489fa4eac158eb88
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