chengjingfeng / gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

gpt-2

Code from the paper "Language Models are Unsupervised Multitask Learners".

We have currently released small (117M parameter) and medium (345M parameter) versions of GPT-2. While we have not released the larger models, we have released a dataset for researchers to study their behaviors.

See more details in our blog post.

Usage

This repository is meant to be a starting point for researchers and engineers to experiment with GPT-2.

Some caveats

• GPT-2 models' robustness and worst case behaviors are not well-understood. As with any machine-learned model, carefully evaluate GPT-2 for your use case, especially if used without fine-tuning or in safety-critical applications where reliability is important.
• The dataset our GPT-2 models were trained on contains many texts with biases and factual inaccuracies, and thus GPT-2 models are likely to be biased and inaccurate as well.
• To avoid having samples mistaken as human-written, we recommend clearly labeling samples as synthetic before wide dissemination. Our models are often incoherent or inaccurate in subtle ways, which takes more than a quick read for a human to notice.

Work with us

Please let us know if you’re doing interesting research with or working on applications of GPT-2! We’re especially interested in hearing from and potentially working with those who are studying

• Potential malicious use cases and defenses against them (e.g. the detectability of synthetic text)
• The extent of problematic content (e.g. bias) being baked into the models and effective mitigations

Development

See DEVELOPERS.md

Contributors

See CONTRIBUTORS.md

Citation

Please use the following bibtex entry:

@article{radford2019language,
  title={Language Models are Unsupervised Multitask Learners},
  author={Radford, Alec and Wu, Jeff and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya},
  year={2019}
}

Future work

We may release code for evaluating the models on various benchmarks.

We are still considering release of the larger models.

License

MIT