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