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OpenAssistant Conversations

Human-chat style data, useful for instruction-tuned LLMs.

About Dataset

OpenAssistant Conversations (OASST1) is a curated dataset of human-written and human-reviewed conversational data created by the OpenAssistant project. The dataset consists of multi-turn dialogue trees where human contributors write prompts and assistant responses, which are then ranked and reviewed by other humans. This structured approach ensures higher quality and consistency compared to raw scraped conversations. The dataset covers a broad range of tasks, including question answering, reasoning, summarization, coding assistance, and general instruction following.

Purpose of Dataset

The Dataset Is Primarily Used For Training And Evaluating Instruction-following And Chat-based Large Language Models. Its Human Preference Annotations Make It Valuable For Supervised Fine-tuning And Reinforcement Learning From Human Feedback (Rlhf). Researchers Use Oasst1 To Improve Response Helpfulness, Safety, And Alignment. It Is Also Widely Used As A Benchmark Dataset For Comparing Conversational Ai Systems And Studying Human Preference Modeling In Ai Alignment Research.