SurgeGlobal/Orca

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## Dataset Generation - Base Model: h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v2 - Seed Instructions: Derived from the FLAN-v2 Collection. - Generation Approach: Explanation tuning with detailed responses generated from h2ogpt-gm-oasst1-en-2048-falcon-40b-v2. - Total Instructions: 5,507 explanation tuning data samples. ### Dataset Sources - Repository: Bitbucket Project - Paper : Pre-Print ## Structure The dataset entries consist of: - Query - Response - System Message (when applicable) ## Usage The Orca Dataset is intended for fine-tuning language models to not only imitate the style but also the reasoning process of LFMs, thereby improving the safety and quality of the models’ responses. ## Citation If you find our work useful, please cite our paper as follows: `` @misc{surge2024openbezoar, title={OpenBezoar: Small, Cost-Effective and Open Models Trained on Mixes of Instruction Data}, author={Chandeepa Dissanayake and Lahiru Lowe and Sachith Gunasekara and Yasiru Ratnayake}, year={2024}, eprint={2404.12195}, archivePrefix={arXiv}, primaryClass={cs.CL} } `` ## Dataset Authors Chandeepa Dissanayake, Lahiru Lowe, Sachith Gunasekara, and Yasiru Ratnayake