A Package for running prompt decoders like RankVicuna
Project description
RankLLM
We offer a suite of prompt decoders, albeit with a current focus on RankVicuna. Some of the code in this repository is borrowed from RankGPT!
Releases
current_version = 0.1.0
📟 Instructions
More instructions to be added soon!
🦙🐧 Model Zoo
The following is a table of our models hosted on HuggingFace:
Model Name | Hugging Face Identifier/Link |
---|---|
RankZephyr 7B V1 - Full - BF16 | castorini/rank_zephyr_7b_v1_full |
RankVicuna 7B - V1 | castorini/rank_vicuna_7b_v1 |
RankVicuna 7B - V1 - No Data Augmentation | castorini/rank_vicuna_7b_v1_noda |
RankVicuna 7B - V1 - FP16 | castorini/rank_vicuna_7b_v1_fp16 |
RankVicuna 7B - V1 - No Data Augmentation - FP16 | castorini/rank_vicuna_7b_v1_noda_fp16 |
✨ References
If you use RankLLM, please cite the following relevant papers:
@ARTICLE{pradeep2023rankvicuna,
title = {{RankVicuna}: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models},
author = {Ronak Pradeep and Sahel Sharifymoghaddam and Jimmy Lin},
year = {2023},
journal = {arXiv:2309.15088}
}
[2312.02724] RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!
@ARTICLE{pradeep2023rankzephyr,
title = {{RankZephyr}: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!},
author = {Ronak Pradeep and Sahel Sharifymoghaddam and Jimmy Lin},
year = {2023},
journal = {arXiv:2312.02724}
}
🙏 Acknowledgments
This research is supported in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada.
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