Instructions to use ProbeX/Model-J__DINO__model_idx_0398 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_0398 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_0398") 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_0398") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0398", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a8561325389ba2b1ab513eee9ede91b9b1d475848609350506323ade50ea0d8
- Size of remote file:
- 5.37 kB
- SHA256:
- 9feeda22abed951fd011ee7614e88aee56b19985339e8ae6efb7a64ea73d87d2
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