Instructions to use ProbeX/Model-J__DINO__model_idx_0201 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_0201 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_0201") 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_0201") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0201") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88add3b034a49d416f9f0d896a29a1aa58fc12dbb58fa5160cb0dd3b03c92583
- Size of remote file:
- 343 MB
- SHA256:
- 898611c58950e97e0cabf5b80bd3afadf2e18a9cb02520b941aaa6fa62378f08
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