Instructions to use ProbeX/Model-J__DINO__model_idx_0235 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_0235 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_0235") 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_0235") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0235", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb5dd1f55bc48b143f7d076f1f042eea53759624f089dec6fde3233d99065a72
- Size of remote file:
- 5.37 kB
- SHA256:
- 30f8f84999c463b7e070e70e4c3b218a8cd88e65a542c81e799b1d7594a80cfa
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