princeton-nlp/SWE-bench_Lite_oracle
Dataset Summary SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 300 test Issue-Pull Request pairs from 11 popular Python. Evaluation is performed by unit test verification using post-PR behavior as the reference solution. The dataset was released as part of SWE-bench: Can Language Models Resolve Real-World GitHub Issues? This dataset SWE-bench_Lite_oracle includes a formatting of each instance using the "Oracle"… See the full description on the dataset page: https://huggingface.co/datasets/princeton-nlp/SWE-bench_Lite_oracle.
| Author / organization | princeton-nlp |
|---|---|
| Downloads | 484 (as reported by Hugging Face) |
| Likes | 4 |
| Created | 19 March 2024 |
| Last updated at source | 15 April 2024 |
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- 17 Oct 2026 Description: Dataset Summary SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 300 test Issue-Pull Request pairs from 11 popular Python. Evaluation is performed by unit test verification using → Dataset Summary SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 300 test Issue-Pull Request pairs from 11 popular Python. Evaluation is performed by unit test verification using
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