Instructions to use ProbeX/Model-J__DINO__model_idx_0529 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_0529 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_0529") 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_0529") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0529", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4032ae46535140f8c10715884d290a9909c200a7e5442bd1ac9036bd6a16f4d
- Size of remote file:
- 5.37 kB
- SHA256:
- d10f6ab85acbde667867be1e0a3d249347c4b86c645d01fd7f6821c36fe4f8ae
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