Instructions to use ProbeX/Model-J__DINO__model_idx_0334 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_0334 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_0334") 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_0334") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0334") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab5dfd55d17fda826cf635524c9ba90128354a95cffc3eec89530f69c9cc5843
- Size of remote file:
- 5.37 kB
- SHA256:
- 9382267fa93659b840ae66d7c110c12af97bf7d153a09d725eb9121dd868af8e
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