Instructions to use ProbeX/Model-J__DINO__model_idx_0264 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_0264 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_0264") 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_0264") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0264", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe59c340f244e72745af9608e9d2c95b1cc05f6b7391cb1bc97e2e6b0687546b
- Size of remote file:
- 5.37 kB
- SHA256:
- f7b9604cd12db864c4238003270669754ba07fced6cb6e441a75db350b4912d0
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