Instructions to use ProbeX/Model-J__DINO__model_idx_0445 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_0445 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_0445") 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_0445") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0445") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c07f6fb775cb910d9ad475bc433b89724b322b1167f161dd9053b93691237921
- Size of remote file:
- 5.37 kB
- SHA256:
- c0b9f1a81ba2c382c3e65e7fcf47f5f58e8531a1aea204e278c76ce09394cf55
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