Instructions to use ProbeX/Model-J__DINO__model_idx_0083 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_0083 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_0083") 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_0083") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0083", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12cf032a888e31b0695d4747ea3d44021ba6dfe448f11fa13876ef5ffdade9e1
- Size of remote file:
- 5.37 kB
- SHA256:
- 2fe43523b8ff83f72f1a8c92a335adc09122b9fadbc0de37ee3717e0231bc890
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