Instructions to use ProbeX/Model-J__DINO__model_idx_0743 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_0743 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_0743") 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_0743") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0743", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cf2d6ca4fd5686704458156df3c059fa49b9e2f24d6a7565df314b152484601
- Size of remote file:
- 343 MB
- SHA256:
- 5360acb1037a923f0cf1c28801ffcf680783e4b28e544cad319e4e89c19e8139
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