SakanaAI_-_Llama-3-8B-Instruct-Coding-Expert-8bits

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Llama-3-8B-Instruct-Coding-Expert - bnb 8bits

• Model creator: https://huggingface.co/SakanaAI/
• Original model: https://huggingface.co/SakanaAI/Llama-3-8B-Instruct-Coding-Expert/

Original model description:

language:

• en library_name: transformers pipeline_tag: text-generation license: llama3 model_type: llama

---

🐟 Llama-3-CycleQD

🤗 Models | 📚 Paper | 🐦 Twitter

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:

• SakanaAI/Llama-3-8B-Instruct-DB-Expert
• SakanaAI/Llama-3-8B-Instruct-OS-Expert
• SakanaAI/Llama-3-8B-Instruct-Coding-Expert

Please refer to our report for more details. We are grateful to the developers of the following source model and training data:

• Llama-3-8B-Instruct
• Agent-FLAN
• Magicoder-Evol-Instruct-110K
• Magicoder-OSS-Instruct-75K

<!-- ## Model Index | Model | Link | |---|---| | DB expert | [SakanaAI/Llama-3-8B-Instruct-DB-Expert](https://huggingface.co/SakanaAI/Llama-3-8B-Instruct-DB-Expert) | | OS expert | [SakanaAI/Llama-3-8B-Instruct-OS-Expert](https://huggingface.co/SakanaAI/Llama-3-8B-Instruct-OS-Expert) | | Coding Expert | [SakanaAI/Llama-3-8B-Instruct-Coding-Expert](https://huggingface.co/SakanaAI/Llama-3-8B-Instruct-Coding-Expert) | | CycleQD | [SakanaAI/Llama-3-8B-Instruct-CycleQD-CS](https://huggingface.co/SakanaAI/Llama-3-8B-Instruct-CycleQD-CS) | -->

Model Details

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• Developed by: Sakana AI
• Model type: Autoregressive Language Model
• License: META LLAMA 3 COMMUNITY LICENSE
• Repository: SakanaAI/CycleQD
• Paper: https://arxiv.org/abs/2410.14735

Uses

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.

Acknowledgement

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.

Citation

@article{sakana2024cycleQD,
  title={Agent Skill Acquisition for Large Language Models via CycleQD},
  author={So Kuroki and Taishi Nakamura and Takuya Akiba and Yujin Tang},
  year={2024},
  eprint={2410.14735},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2410.14735},
}