Instructions to use ProbeX/Model-J__DINO__model_idx_0199 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_0199 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_0199") 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_0199") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0199", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86afd45d0263c6e3af41d71e8d15195098eee387326f1fccbddfc77fb1216305
- Size of remote file:
- 5.37 kB
- SHA256:
- 5efc877986b0f5be908e6efaa8e3498fc851a13b213e26a520aa4608a486aace
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