Instructions to use ProbeX/Model-J__DINO__model_idx_0109 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_0109 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_0109") 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_0109") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0109") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 030d713e046ee4c905e1493e0f45dc04c35a35556a986b92d66c79bb8a13f252
- Size of remote file:
- 5.37 kB
- SHA256:
- a240aecbc9fe562a791d228adf20863035c768bb76906c2e6d552fe3d20c3427
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