Quantization made by Richard Erkhov.
This collection of agentic Language Models (LLMs) is based on Llama-3-8B-Instruct.
Llama-3-8B-Instruct-CycleQD-CS is created using the CycleQD method, which leverages:
Please refer to our
report for more details.
We are grateful to the developers of the following source model and training data:
This model is provided for research and development purposes only and should be considered as an experimental prototype.
It is not intended for commercial use or deployment in mission-critical environments.
Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed.
Sakana AI shall not be liable for any direct, indirect, special, incidental, or consequential damages, or any loss arising from the use of this model, regardless of the results obtained.
Users must fully understand the risks associated with the use of this model and use it at their own discretion.
We would like to thank the developers of the source models and training datasets for their contributions and for making their work available. These models are based on results obtained from a project, JPNP20017, subsidized by the New Energy and Industrial Technology Development Organization (NEDO), and built with Meta Llama 3.
1@article{sakana2024cycleQD,
2 title={Agent Skill Acquisition for Large Language Models via CycleQD},
3 author={So Kuroki and Taishi Nakamura and Takuya Akiba and Yujin Tang},
4 year={2024},
5 eprint={2410.14735},
6 archivePrefix={arXiv},
7 primaryClass={cs.CL},
8 url={https://arxiv.org/abs/2410.14735},
9}
