We release world’s first datasets for training software engineering agents🔥 More specifically, our AI R&D team uploaded two datasets to @HuggingFace: one with 6,411 Issue-PR pairs, and the other with 80,036 agent trajectories. Learn more on our blog: eu1.hubs.ly/H0fwMB00

As a follow up to our work on applying search to software engineering agents, today we are releasing datasets of problem instances and agent trajectories. This is the training data we previously used to achieve 40.6% on SWE-bench Verified using open-weight models only! 🧵⬇️

Spirit of open-source is in the air thanks to DeepSeek! And today we are happy to release kvax, our implementation of flash attention for jax! It is very fast and has some advanced features such as context parallelism support that might not be easy to come by. Details ⬇️

An extended writeup of our earlier research blogpost on training critics for SWE agents has been accepted to ICML! Some details below ⬇️

Our own SWE-rebench just became the #1 most downloaded dataset on @HuggingFace 🥇 SWE-rebench is a dataset and benchmark for code agents based on LLMs, developed by our AI R&D team. It has been downloaded more than 3.9M times — 3.1M in the last month. 1/4