SurgeGlobal/Evol-Instruct

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## Dataset Generation - Base Model: h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v2 - Seed Instructions: Selected from the databricks/databricks-dolly-15k dataset - Generation Approach: Iterative evolution of instructions using a conversational syntax for in-depth and in-breadth evolving - Total Instructions: 2,304 instruction tuning data samples ### Dataset Sources - Repository: Bitbucket Project - Paper: Pre-Print ### Structure The dataset entries consist of: - Instruction - Response - Evolution Strategy (in-depth or in-breadth) - Category (of the original instruction) ### Usage The Evol-Instruct Dataset is designed for the automatic evolution of instruction datasets, enhancing the complexity and diversity of instructions to train language models for a wide range of tasks. ## 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