Instructions to use ProbeX/Model-J__DINO__model_idx_0207 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_0207 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_0207") 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_0207") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0207") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf252d894689081067def5501f044e06657c3187f208927c133c47651a239bd3
- Size of remote file:
- 5.37 kB
- SHA256:
- e6f5d0de52467c59d7329ac0c59e237e92e69a90796b5b229ebc6e272883db00
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