Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Agora's open source implementation of the paper: Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Installation
You can install the package using pip
Citation
@misc{2309.08532,
Author = {Qingyan Guo and Rui Wang and Junliang Guo and Bei Li and Kaitao Song and Xu Tan and Guoqing Liu and Jiang Bian and Yujiu Yang},
Title = {Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers},
Year = {2023},
Eprint = {arXiv:2309.08532},
}
1 maintainer
Metadata
1 maintainer
Release files for eaot 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| eaot-0.0.1.tar.gz | 2.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| eaot-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.8 kB
Release files / eaot-0.0.1.tar.gz
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Release files / eaot-0.0.1-py3-none-any.whl
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| Size | 2.4 kB |
| Tags | Python 3 |
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