---
library_name: transformers
pipeline_tag: text-generation
---

# Hybrid Policy Distillation for LLMs

This repository contains the weights for the model described in the paper [Hybrid Policy Distillation for LLMs](https://huggingface.co/papers/2604.20244).

Hybrid Policy Distillation (HPD) is a framework for compressing large language models (LLMs) that reformulates knowledge distillation (KD) as a reweighted log-likelihood objective at the token level. It integrates the complementary advantages of forward and reverse KL to balance mode coverage and mode-seeking, demonstrating improved computational efficiency and final performance across diverse model families and scales.

## Resources
- **Paper:** [Hybrid Policy Distillation for LLMs](https://huggingface.co/papers/2604.20244)
- **Code:** [GitHub Repository](https://github.com/zwhong714/Hybrid-Policy-Distillation)

## Citation

If you find this work useful in your research, please cite:

```bibtex
@article{hong2024hybrid,
  title={Hybrid Policy Distillation for LLMs},
  author={Hong, Zhiwei and others},
  journal={arXiv preprint arXiv:2604.20244},
  year={2024}
}
```