title: The ShareLM Collection and Plugin: Contributing Human-Model Chats for
    the Benefit of the Community
summary: Human-model conversations provide a window into users' real-world scenarios,
  behavior, and needs, and thus are a valuable resource for model development and
  research. While for-profit companies collect user data through the APIs of
  their models, using it internally to improve their own models, the open source
  and research community lags behind.
    We introduce the ShareLM collection, a unified set of human conversations
  with large language models, and its accompanying plugin, a Web extension for
  voluntarily contributing user-model conversations. Where few platforms share
  their chats, the ShareLM plugin adds this functionality, thus, allowing users
  to share conversations from most platforms. The plugin allows the user to rate
  their conversations, both at the conversation and the response levels, and
  delete conversations they prefer to keep private before they ever leave the
  user's local storage. We release the plugin conversations as part of the
  ShareLM collection, and call for more community effort in the field of open
  human-model data.
    The code, plugin, and data are available.
paper_authors._id: 66bf3d59d9a797412265dc27
paper_authors.name: Shachar Don-Yehiya
paper_authors._id: 66bf3d59d9a797412265dc28
paper_authors.name: Leshem Choshen
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-08-19T22:13:31.817Z
paper_authors._id: 61bf40824b4300d0fb0acf59
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1644224872623-61bf40824b4300d0fb0acf59.jpeg
paper_authors.fullname: Leshem Choshen
paper_authors.type: user
paper_authors.user: borgr
paper_authors._id: 66bf3d59d9a797412265dc29
paper_authors.name: Omri Abend
paper_title: The ShareLM Collection and Plugin: Contributing Human-Model Chats for
    the Benefit of the Community
paper_summary: Human-model conversations provide a window into users' real-world scenarios,
  behavior, and needs, and thus are a valuable resource for model development and
  research. While for-profit companies collect user data through the APIs of
  their models, using it internally to improve their own models, the open source
  and research community lags behind.
    We introduce the ShareLM collection, a unified set of human conversations
  with large language models, and its accompanying plugin, a Web extension for
  voluntarily contributing user-model conversations. Where few platforms share
  their chats, the ShareLM plugin adds this functionality, thus, allowing users
  to share conversations from most platforms. The plugin allows the user to rate
  their conversations, both at the conversation and the response levels, and
  delete conversations they prefer to keep private before they ever leave the
  user's local storage. We release the plugin conversations as part of the
  ShareLM collection, and call for more community effort in the field of open
  human-model data.
    The code, plugin, and data are available.
paper_ai_summary: The ShareLM collection and plugin facilitate the voluntary sharing and rating of human-large language model conversations, enhancing open-source model development.
paper_ai_keywords: large language models ShareLM collection Web extension human-model conversations conversation rating data collection