Instructions to use stanfordmimi/Merlin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Merlin
How to use stanfordmimi/Merlin with Merlin:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Updating paper with nature paper
Browse files
README.md
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pipeline_tag: text-to-image
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---
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# Merlin:
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[](https://pypi.org/project/merlin-vlm/)
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Merlin is a 3D VLM for computed tomography that leverages both structured electronic health records (EHR) and unstructured radiology reports for pretraining. The huggingface repository here provides the model weights and an example image file.
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[[💻 Github](https://github.com/StanfordMIMI/Merlin)] [[📄 Paper](https://
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## ⚡️ Installation
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```
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## 📎 Citation
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If you find this repository useful for your work, please cite the cite the [
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```bibtex
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@article{
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journal=
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}
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```
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pipeline_tag: text-to-image
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---
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# Merlin: A Computed Tomography Vision–Language Foundation Model and Dataset
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[](https://doi.org/10.1038/s41586-026-10181-8) [](https://pypi.org/project/merlin-vlm/)
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Merlin is a 3D VLM for computed tomography that leverages both structured electronic health records (EHR) and unstructured radiology reports for pretraining. The huggingface repository here provides the model weights and an example image file.
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[[💻 Github](https://github.com/StanfordMIMI/Merlin)] [[📄 Nature Paper](https://www.nature.com/articles/s41586-026-10181-8)]
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## ⚡️ Installation
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```
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## 📎 Citation
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If you find this repository useful for your work, please cite the cite the [Nature paper](https://www.nature.com/articles/s41586-026-10181-8):
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```bibtex
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@article{blankemeier_kumar2026merlin,
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author = {Blankemeier, Louis and Kumar, Ashwin and Cohen, Joseph Paul and Liu, Jiaming and Liu, Longchao and Van Veen, Dave and Gardezi, Syed Jamal Safdar and Yu, Hongkun and Paschali, Magdalini and Chen, Zhihong and Delbrouck, Jean-Benoit and Reis, Eduardo and Holland, Robbie and Truyts, Cesar and Bluethgen, Christian and Wu, Yufu and Lian, Long and Jensen, Malte Engmann Kjeldskov and Ostmeier, Sophie and Varma, Maya and Valanarasu, Jeya Maria Jose and Fang, Zhongnan and Huo, Zepeng and Nabulsi, Zaid and Ardila, Diego and Weng, Wei-Hung and Amaro Junior, Edson and Ahuja, Neera and Fries, Jason and Shah, Nigam H. and Zaharchuk, Greg and Willis, Marc and Yala, Adam and Johnston, Andrew and Boutin, Robert D. and Wentland, Andrew and Langlotz, Curtis P. and Hom, Jason and Gatidis, Sergios and Chaudhari, Akshay S.},
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title = {Merlin: a computed tomography vision-language foundation model and dataset},
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journal = {Nature},
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year = {2026},
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doi = {10.1038/s41586-026-10181-8},
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url = {https://doi.org/10.1038/s41586-026-10181-8}
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}
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```
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