Instructions to use ProbeX/Model-J__DINO__model_idx_0175 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_0175 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_0175") 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_0175") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0175") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f0a57f22b76e5b693b2a413067e830e94ecc240e81958e3f75871a515a589fd
- Size of remote file:
- 5.37 kB
- SHA256:
- 4804ff9a0498e361cb7c40d887514e8daa74c7f545412f838d04bd449bbd9ab3
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