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---
license: apache-2.0
datasets:
- OpenAssistant/oasst1
language:
- en
---
## ๐ Humback
The proposed Humback is a novel framework that can augment the instruction data for supervised fine-tuning with high quality.
This is a SFT (supervised fine-tuning) model $M_{0}$ for [Humback](https://arxiv.org/pdf/2308.06259.pdf) reproduction.
This model is trained on the seed data.
The seed data is a sampled dataset from [oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1).
You may find more details and usage examples in [Spico197/Humback](https://github.com/Spico197/Humback) .
## ๐ Reference
```bibtex
@misc{li2023selfalignment,
title={Self-Alignment with Instruction Backtranslation},
author={Xian Li and Ping Yu and Chunting Zhou and Timo Schick and Luke Zettlemoyer and Omer Levy and Jason Weston and Mike Lewis},
year={2023},
eprint={2308.06259},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
``` |