Instructions to use ProbeX/Model-J__DINO__model_idx_0135 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_0135 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_0135") 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_0135") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0135", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8286d352f9cbc238e748f2b532ee1ae64ac41f2b9a95d7c4be222c69a97a1a44
- Size of remote file:
- 5.37 kB
- SHA256:
- 5156ab602cb70ce7713ba7800b95f17bcfa9caaab64fa3bfd752f25a0d10cddc
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