Instructions to use stevetod/doduo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevetod/doduo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="stevetod/doduo", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stevetod/doduo", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: mit
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license: mit
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# Doduo: Dense Visual Correspondence from Unsupervised Semantic-Aware Flow
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[Zhenyu Jiang](http://zhenyujiang.me), [Hanwen Jiang](https://hwjiang1510.github.io/), [Yuke Zhu](https://www.cs.utexas.edu/~yukez/)
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University of Texas at Austin
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