Instructions to use ProbeX/Model-J__DINO__model_idx_0086 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_0086 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_0086") 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_0086") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0086", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02f98d35ddf49e6d44080b1bf626ec76731d9c7f57660b2e1fd77257d901b4fd
- Size of remote file:
- 5.37 kB
- SHA256:
- 9e8f14f3489bf5b56ced7bee5d68d5f3d216f16d5d7d040dcf33fde64e462ba4
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