Instructions to use ProbeX/Model-J__DINO__model_idx_0392 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_0392 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_0392") 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_0392") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0392") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b57acfe710cc2482b4d265b281aa900cf44c675a87bb5de4ff88c57db34b3be
- Size of remote file:
- 5.37 kB
- SHA256:
- aa37a6caa5433e219cc9b285ba38983e3d50260b211f0f822f2c0e8c580a4f70
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