Instructions to use ProbeX/Model-J__DINO__model_idx_0892 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_0892 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_0892") 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_0892") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0892", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d3e5201f171a15181abc6daa3a83d47d4a5c06da11745c3f4e28229296d3a24
- Size of remote file:
- 5.37 kB
- SHA256:
- 8552415f264f1ad1f240ad5bb193ac4a0f209811ee07085205d7deb5c7af0797
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