Instructions to use ProbeX/Model-J__DINO__model_idx_0449 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_0449 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_0449") 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_0449") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0449", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fce23c00870442e23c05b5141d341cc1c69a035c116ff573f540ee419036450
- Size of remote file:
- 343 MB
- SHA256:
- 2dfe87110b094103231a7a24f59e716c062d9b62c35b87e3e7b44aaf2cb44708
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