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@@ -180,7 +180,7 @@ The legal basis for data collection under fair use and with regards to GDPR and
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  **Between implicit and explicit consent** One of the goals of BigCode is to give developers agency over their source code and let them decide whether or not it can be used to develop and evaluate LLMs. Software developers typically rely on licenses to express how they want their work to be re-used; in particular, developers who choose Open Source licenses often do so because they want their code to be broadly re-used. This motivated us to start by selecting data from repositories that met the following criteria:
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- * The repository has an open source licensed attached - open source, while chosen for very different reasons by different people, typically indicates a willingness to have one's work reused or adapted
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  * The license does not have an attribution clause - attribution is a difficult technical problem for code LLMs. Since we cannot guarantee that the model will be used in a way that attributes its generations to specific training data in a way that satisfies the intent of the licensor, we chose to only keep licenses without an attribution clause
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  Selecting repositories based on licenses is only the first step, however, as many of these licenses were chosen before the recent developments in code LLMs. Thus, we complement this initial approach by also giving repository owners the ability to **opt out** of having their repositories included in The Stack. We see this approach as a meaningful step forward in improving the agency of data subject in the development of code LLMs, and we present both the tools we developed to support it and its known limitations in the rest of this section.
 
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  **Between implicit and explicit consent** One of the goals of BigCode is to give developers agency over their source code and let them decide whether or not it can be used to develop and evaluate LLMs. Software developers typically rely on licenses to express how they want their work to be re-used; in particular, developers who choose Open Source licenses often do so because they want their code to be broadly re-used. This motivated us to start by selecting data from repositories that met the following criteria:
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+ * The repository has an open source license attached - open source, while chosen for very different reasons by different people, typically indicates a willingness to have one's work reused or adapted
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  * The license does not have an attribution clause - attribution is a difficult technical problem for code LLMs. Since we cannot guarantee that the model will be used in a way that attributes its generations to specific training data in a way that satisfies the intent of the licensor, we chose to only keep licenses without an attribution clause
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  Selecting repositories based on licenses is only the first step, however, as many of these licenses were chosen before the recent developments in code LLMs. Thus, we complement this initial approach by also giving repository owners the ability to **opt out** of having their repositories included in The Stack. We see this approach as a meaningful step forward in improving the agency of data subject in the development of code LLMs, and we present both the tools we developed to support it and its known limitations in the rest of this section.