SWE-smith scales software engineering training data to 50k instances across 128 repositories, enabling SWE-agent-LM-32B to achieve 40.2% Pass@1 on SWE-bench Verified, state of the art among open-source models.
Figure 20: A copy of the prompt provided to an LM via SWE-agent informing the LM of the nature of the task, the task description itself, and several tips on how to proceed
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SWE-smith: Scaling Data for Software Engineering Agents
SWE-smith scales software engineering training data to 50k instances across 128 repositories, enabling SWE-agent-LM-32B to achieve 40.2% Pass@1 on SWE-bench Verified, state of the art among open-source models.