Instructions to use ProbeX/Model-J__DINO__model_idx_0016 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_0016 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_0016") 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_0016") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0016", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63306cd3317f62ab0a32ac7ad4d188c1bc3f0067e9255526ffafd86d2f52090d
- Size of remote file:
- 5.37 kB
- SHA256:
- f4b8f5b88e64c8648bc63d055a329561a0c505f5fa7ccfae009e482d5443f8a4
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