README.md

---
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 `DUO` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('gpt2')
model = AutoModelForMaskedLM.from_pretrained('s-sahoo/duo-distilled')
```
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)

## 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://huggingface.co/papers/2506.10892).

Project page: https://s-sahoo.com/duo

## Citation

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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)