Datasets:
|
Download README.md from code2lora/code2lora-static: direct link, hf CLI and curl.
- Browser
- Download file 1.73 kB
-
https://huggingface.co/datasets/code2lora/code2lora-static/resolve/68ad91b7b0de12fde1cdf00a73d5484cbc075c09/README.md
- Command line
-
hf download hf://datasets/code2lora/code2lora-static@68ad91b7b0de12fde1cdf00a73d5484cbc075c09/README.md
-
curl -L -o README.md https://huggingface.co/datasets/code2lora/code2lora-static/resolve/68ad91b7b0de12fde1cdf00a73d5484cbc075c09/README.md
1.73 kB
| license: mit | |
| pretty_name: Code2LoRA-Static (static track, single snapshot) | |
| tags: [code, assertion-completion, repository-level] | |
| configs: | |
| - config_name: qna | |
| data_files: | |
| - {split: train, path: qna/train.parquet} | |
| - {split: cr_val, path: qna/cr_val.parquet} | |
| - {split: cr_test, path: qna/cr_test.parquet} | |
| - {split: ir_val, path: qna/ir_val.parquet} | |
| - {split: ir_test, path: qna/ir_test.parquet} | |
| - config_name: repos | |
| data_files: | |
| - {split: train, path: repos/train.parquet} | |
| - {split: cr_val, path: repos/cr_val.parquet} | |
| - {split: cr_test, path: repos/cr_test.parquet} | |
| # Code2LoRA-Static — static track (single snapshot) | |
| The **Static track** of RepoPeftBench exactly as consumed by the paper's | |
| main-results table (`Code2LoRA-Static`, single anchor snapshot per | |
| repository). Contains only the paper-used QnAs (post quality-filter). For | |
| the out-of-distribution slice see `code2lora/repopeftbench-ood`. | |
| | config | split | rows | | |
| |---|---|---:| | |
| | qna | train | 39,612 | | |
| | qna | cr_val | 6,213 | | |
| | qna | cr_test | 6,414 | | |
| | qna | ir_val | 4,833 | | |
| | qna | ir_test | 5,222 | | |
| | repos | train / cr_val / cr_test | 409 / 51 / 52 | | |
| * `qna` — one row per assertion pair (`repo_id, prefix, target, | |
| assertion_type, difficulty, test_file, test_function, test_class, | |
| lineno, commit_idx`). | |
| * `repos` — frozen 2048-d Qwen3-Embedding repo-state vector per repo | |
| (`repo_id, embedding`); IR suites reuse the train-repo embeddings. | |
| ```python | |
| from datasets import load_dataset | |
| qna = load_dataset("code2lora/code2lora-static", "qna") | |
| repos = load_dataset("code2lora/code2lora-static", "repos") | |
| ``` | |
| Companion datasets: `code2lora/code2lora-evo`, | |
| `code2lora/code2lora-static-anchor`, `code2lora/repopeftbench-ood`. | |