Instructions to use ProbeX/Model-J__DINO__model_idx_0873 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_0873 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_0873") 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_0873") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0873", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42475240c4ab71fe899934154eecce13c255c0b61144cf8e4d50d32bc0c06a50
- Size of remote file:
- 5.37 kB
- SHA256:
- 853c4cee976ca08dbfd6c2dc773f4f194d2f463210b04879c12979a5f2bdf63e
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