ShareGPT Conversations

Raw user-chat conversations scraped from ShareGPT.

About Dataset

ShareGPT Conversations is a large collection of raw user–assistant chat conversations scraped from the ShareGPT platform. The dataset captures real-world interactions between users and large language models, covering a wide variety of prompts, questions, follow-up queries, and conversational styles. The data is largely unfiltered, preserving natural conversational flow, including incomplete questions, multi-turn dialogues, and diverse topic domains. As a community-sourced dataset, it reflects how users organically interact with AI systems, rather than curated or scripted conversations. The dataset is text-based and focuses on conversational exchanges, making it especially representative of instruction-following and dialogue-based interactions.

Purpose of Dataset

The Primary Purpose Of Sharegpt Conversations Is To Support Research And Development Of Conversational And Instruction-tuned Language Models. It Is Widely Used For Fine-tuning Llms To Improve Dialogue Coherence, Response Relevance, And Multi-turn Conversational Ability. Researchers Use It To Study User Prompting Behavior, Conversational Patterns, And Real-world Usage Of Ai Assistants. The Dataset Is Also Useful For Benchmarking Conversational Robustness, Understanding Failure Cases, And Improving Alignment With User Intent. It Plays An Important Role In Training Models That Aim To Behave As Helpful, Interactive Assistants Rather Than Single-turn Text Generators.