Instructions to use ProbeX/Model-J__DINO__model_idx_0884 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_0884 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_0884") 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_0884") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0884", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02e6cc4aa3f336bf3a867dc34b157f60c4465fac998d7f0442a59cec8b8be911
- Size of remote file:
- 5.37 kB
- SHA256:
- 761ddf2849fdd3bab33fc46680c7ad9da6eb337920a81704f13c62240fc6bb36
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