Instructions to use ProbeX/Model-J__DINO__model_idx_0711 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_0711 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_0711") 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_0711") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0711", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9107a4d214fbe68333d21ba968d04826bdf6da19b77c677850a44c37057983ef
- Size of remote file:
- 5.37 kB
- SHA256:
- 236640d7661e83edee819efe7d7710692b6b509a3e0fc826cd4a7494803061c2
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