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ShareGPT

As explained in Natural Language Processing in Action, Second Edition

ShareGPT is a dataset of user-provided conversations with ChatGPT used for training and evaluating conversational language models.

ShareGPT is a dataset of user-provided ChatGPT conversations used to fine-tune conversational language models, including Vicuna, for virtual-assistant tasks. Its practical value comes from exposing models to real dialogue rather than relying only on general foundational-model training. section 10.3.13

ShareGPT supports several applied goals:

  • Fine-tune open-source foundational models for domain-relevant conversational behavior. section 10.3.13
  • Build virtual assistants with accuracy approaching larger models while using fewer parameters. section 10.3.13
  • Support evaluation alongside chatbot arenas that compare competing conversational systems. section 10.3.13

Vicuna fine-tuning

Vicuna was trained on 90,000 ShareGPT conversations. In 2023, the dataset contained almost half a million ChatGPT conversations, illustrating its growth as an open conversational-data resource. section 10.3.13

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Describes dataset scale and fine-tuning applications, but does not detail schema, preprocessing, or construction methods.
Examples
Uses 90,000 conversations for Vicuna and nearly half a million ChatGPT conversations reported in 2023.
What you can do after
Apply it via fine-tuning foundational models to improve conversational accuracy and effectiveness.
How it connects
Connects conversational datasets with fine-tuning, foundational models, virtual assistants, open-source models, and reinforcement learning from human feedback.
Cover of Natural Language Processing in Action, Second Edition
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.