--- datasets: - Skylion007/openwebtext language: - en library_name: transformers license: apache-2.0 metrics: - perplexity pipeline_tag: text-generation --- ## Using DUO To use the pre-trained model for masked language modeling, use the following snippet: ```python from transformers import AutoModelForMaskedLM, AutoTokenizer # See the `MDLM` collection page on the hub for list of available models. tokenizer = transformers.AutoTokenizer.from_pretrained('gpt2') model = AutoModelForMaskedLM.from_pretrained('s-sahoo/duo') ``` For a hands-on example, check out this [Colab notebook](https://colab.research.google.com/drive/1Sf7R-dqdR6gq-H8nyZ9E3ZkyvqMTqcwq?usp=sharing). For more information and implementation details, visit our github repository: [DUO](https://github.com/s-sahoo/duo) and project page: [Project Page](https://s-sahoo.com/duo) ## Model Details The model, which has a context length of `1024` and is similar in size to GPT2-medium with approximately `130 million` non-embedding parameters, was trained for 1M steps on the OpenWebText corpus. For more details, please see our paper: [The Diffusion Duality](https://openreview.net/forum?id=CB0Ub2yXjC). ## Citation Please cite our work using the bibtex below: **BibTeX:** ``` @inproceedings{ sahoo2025the, title={The Diffusion Duality}, author={Subham Sekhar Sahoo and Justin Deschenaux and Aaron Gokaslan and Guanghan Wang and Justin T Chiu and Volodymyr Kuleshov}, booktitle={Forty-second International Conference on Machine Learning}, year={2025}, url={https://openreview.net/forum?id=9P9Y8FOSOk} } ``` ## Model Card Contact Subham Sekhar Sahoo (ssahoo@cs.cornell.edu)