Instructions to use ProbeX/Model-J__DINO__model_idx_0142 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_0142 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_0142") 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_0142") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0142", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98459ef052ea7997e1f976308ed612354d57923b8074f57ff9176fcab5415511
- Size of remote file:
- 343 MB
- SHA256:
- 66a28619a7faa96a3fe14b10a456bb752b5f8289fa6d6334733f71f5b15df787
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