Instructions to use ProbeX/Model-J__DINO__model_idx_0996 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_0996 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_0996") 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_0996") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0996", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf4601e569186ce599d385dd3cbb05a99880ed999cfdb49a10ccff287cb53609
- Size of remote file:
- 5.37 kB
- SHA256:
- f1129394f58269067ed9768d06afc4dac8584384b3a22b086295918f9488feaa
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