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