swesmith
swesmith-nl2bash-stack-bugsseqnl2bash-swesmith-stack-bugsseqqwen35-9b-swesmithGLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthinksft_GLM-4-7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k_Qwen3-32Bswe-agent-lm-7b-num07-swesmitha3-rl-SankalpKJ_swesmith-oracle-filtered-40-8Bswesmith-coldstart-rl-seqnorm-tis-pym2t-75-8B
Datasets
All datasets matching “swesmith”SWE-smith
SWE-smith Dataset
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[12/14/2025] NOTE: We will no longer actively update this dataset.
While this dataset is still functional and usable, we recommend you use the `SWE-bench/SWE-smith-[lang]` datasets.
For better maintainability and ease-of-use, we are maintaining language-specific datasets in lieu of this mono-repo.
The SWE-smith Dataset is a training dataset of 50137 task instances from 128 GitHub repositories, collected using the SWE-smith toolkit.… See the full description on the dataset page: https://huggingface.co/datasets/SWE-bench/SWE-smith.SWE-smith-py
SWE-smith Dataset
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As of 12/14/2025, SWE-smith: Python contains 50908 task instances from 131 GitHub repositories
The SWE-smith Dataset is the largest open source dataset for training software engineering agents.
All SWE-smith task instances come with an executable environment.
To learn more about how to use this dataset to train Language Models for Software Engineering, please refer to the documentation.
SWE-smith-javaSWE-smith-pythonSWE-smith2SWE-smith-trajectories
SWE-smith Trajectories
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This dataset contains the 5017 trajectories we fine-tuned Qwen 2.5 Coder Instruct on, leading to
SWE-agent-LM-32B, a coding LM agent that
achieve 40.2% on SWE-bench Verified (no verifiers or multiple rollouts, just 1 attempt per instance).
Trajectories were generated by running SWE-agent + Claude 3.7 Sonnet on task instances from
the SWE-smith dataset.