BigCode Project Governance Card

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 This document serves as an overview of the different mechanisms and areas of governance in the BigCode project. You can also find a version of The BigCode Project Governance Card on arXiv .
It aims to support transparency by providing relevant information about choices that were made during the project to the broader public,
and to serve as an example of intentional governance of an open research project that future endeavors can leverage to shape their own approach.
The first section, Project Structure , covers the project organization, its stated goals and values, its internal decision processes, and its funding and resources.
The second section, Data and Model Governance , covers decisions relating to the questions of data subject consent, privacy, and model release.

 
 
 
 
 
 1. Project Structure
 

 
 
 
 
 
 1.a. Goals and Values
 

 
 
 
 
 
 Project Overview
 

 BigCode is an open scientific collaboration working on the responsible development and use of large language models for code, aiming to empower the machine learning and open source communities through open governance.

 Code LLMs enable the completion and synthesis of code, both from other code snippets and natural language descriptions, and can be used across a wide range of domains, tasks, and programming languages. These models can, for example, assist professional and citizen developers with building new applications.

 One of the challenges typically faced by researchers working on code LLMs is the lack of transparency around the development of these systems. While a handful of papers on code LLMs have been published, they do not always give full insight into the development process, which hinders both external accountability and the ability of all but a few well funded research labs to meaningfully participate in shaping the technology. 

 BigCode is a community project jointly led by Hugging Face and ServiceNow. Both organizations committed research, engineering, ethics, governance, and legal resources to ensure that the collaboration runs smoothly and makes progress towards the stated goals. ServiceNow Research and Hugging Face have made their respective compute clusters available for large-scale training of the BigCode models, and Hugging Face hosts the datasets, models, and related applications from the community to make it easy for everyone to access and use.

 An open-invitation was extended to the global AI research community to join forces on the development of state-of-the-art code LLMs, with a focus on research topics such as:

 
 Constructing a representative evaluation suite for code LLMs, covering a diverse set of tasks and programming languages

 Developing new methods for faster training and inference of LLMs

 The legal, ethics, and governance aspects of code LLMs

 
 The BigCode project is conducted in the spirit of open science

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