Instructions to use ProbeX/Model-J__DINO__model_idx_0780 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_0780 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_0780") 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_0780") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0780", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91efa5f428173ac80d7fb2f510b51c9fc0a86f3bd303aa86da202b54f5a37725
- Size of remote file:
- 5.37 kB
- SHA256:
- 68885be4029c59c559881e6e42e5932e526ab3ddbe1456c9f5f5111e855306fd
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