Instructions to use ProbeX/Model-J__DINO__model_idx_0904 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_0904 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_0904") 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_0904") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0904") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ea15e0975cd857675f21971fd86bd294c4a2f6635cbdfdc9e950f2d5c671e93
- Size of remote file:
- 5.37 kB
- SHA256:
- fda70e42049b12222b1c7e9ae8dcf01e673ac58e039d5b25ccddd9a9bda70f19
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