Sera-4.5A-Lite-T2

This dataset contains 35615 trajectories. Data was generated from the *second* rollout of SVG on 121 SWE-smith codebases using GLM-4.5-Air as teacher and includes one SVG run per function. 16000 samples from the dataset were used to train SERA-32B-GA. [Sera-4.5-Full-T2](https://huggingface.co/datasets/allenai/Sera-4.5A-Full-T2) is a superset of this dataset with three SVG runs per function. **Schema**: ``` messages: Generated trajectory instance_id: ID of trajectory rollout_patch: Created patch to the codebase from the current trajectory func_name: Name of function sampled from codebase to start the pipeline func_path: File path to the sampled function line_level_recall: Minimum patch verification threshold that is satisfied problem_statement: Problem statement provided to the model target_patch: Ground truth patch (empty if T1) docker_image: Docker image used ``` **Verification**: Verification can be done on T2 trajectories by comparing generated rollout patches against the target ground truth patch from T1 trajectories. We do not verify in our main experiments but provide the metadata to do so in `target_patch` and `rollout_patch`. **Note**: Apply json.loads() to the messages column to load. Sera-4.5A-Lite-T2 is licensed under the Open Data Commons Attribution License v1.0 (ODC-By). It is intended for research and educational use. For more information, please see our Responsible Use Guidelines.