Instructions to use ProbeX/Model-J__DINO__model_idx_0176 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_0176 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_0176") 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_0176") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0176", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3c4753d760c76bd9187ddbc9b9781bc80cd2ff84fe972565d5b6efc38e380f9
- Size of remote file:
- 5.37 kB
- SHA256:
- d036f912ae98086f29a15f89d55023502cc3d9cdee9ab80cd78b3e1f8c11ecf5
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