Instructions to use ProbeX/Model-J__DINO__model_idx_0537 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_0537 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_0537") 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_0537") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0537", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48b95796edfd481f1bf7f206d340de22b175483a785d73878e6970459b2fcb64
- Size of remote file:
- 5.37 kB
- SHA256:
- 664499158de4bb1a46de6f3adaefe144628f774c822eed22c8e2fa4121b4e584
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