Instructions to use ProbeX/Model-J__DINO__model_idx_0157 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_0157 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_0157") 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_0157") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0157") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 233d7a97e9accd7e917f36efe2e5151fb8a6cb251b899a17e3dd0313b227d8c4
- Size of remote file:
- 5.37 kB
- SHA256:
- 6e5854757f5005481d3c32deaf93b97984e57751b404180933d37649b98018c6
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