Instructions to use ProbeX/Model-J__DINO__model_idx_0853 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_0853 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_0853") 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_0853") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0853", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d19bc2fe14a5b4fabcbb9f954d4009eab21e7af355198779d4c2aec04f42791
- Size of remote file:
- 5.37 kB
- SHA256:
- 7273cdfb2c132d3040e347c8ca8ac609ce85268f397437a057bd243812960ba7
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