Instructions to use ProbeX/Model-J__DINO__model_idx_0994 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_0994 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_0994") 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_0994") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0994") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 007c6ad5508bda97481c1f378d193819efaf6ecb4c411c28d08545722560a552
- Size of remote file:
- 5.37 kB
- SHA256:
- 59d2ef7f654196649b938a8d573ebb6bd4bd0ff024b840d64acf94fbf03863b2
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