Instructions to use ProbeX/Model-J__DINO__model_idx_0781 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_0781 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_0781") 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_0781") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0781", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f7ac7282af68eea01285f73485c4ccc148d892c17e5ef458c0b670d5ec7ebf0
- Size of remote file:
- 343 MB
- SHA256:
- a0861609c2ad8062fc21811bc8b42b1293a7e886cf8567d556bc4a32bed4f648
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