Instructions to use ProbeX/Model-J__DINO__model_idx_0920 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_0920 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_0920") 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_0920") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0920", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ac75c13e42a48cd7323ed14bcaa77f30760ce3e0974522775b46b07e2f1ed8e
- Size of remote file:
- 343 MB
- SHA256:
- 353140245e7b31ea891aeeaf0e827ea0c38d367b7f66f24368d5aaa4396f83a3
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