Impacts and Research
An Economic and Agile
Workforce Solution
System Powered by Fine-Tuned Agents
Atlas outperforms competitors on the SWE-Bench (May 2024) by adopting a novel approach to fine-tuning language models with trajectories from multiple tasks and prompting methods.
Trained on
8400
Real-World Task Trajectories
20.2%
SWE-Bench (On all 2294 Issues)
Supported Languages
Python
Java
TS
C++
Swift
GO
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With its "repo-level query" feature, Atlas accelerates knowledge acquisition for you and your team. By partnering with communities like MiraclePlus (formerly YC China), we provide high-quality learning resources and content recommendations.
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