Instructions to use ProbeX/Model-J__DINO__model_idx_0586 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_0586 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_0586") 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_0586") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0586", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5170bb4c2fa7381cc520fdff289fa51d6b7bd14461d05d5d11dc0b29cb23cd72
- Size of remote file:
- 5.37 kB
- SHA256:
- 42b0e122f969f34620082e61b34c79aa067b028011932a6b7fcf0abc5c4fd4d5
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