Datasets:
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language:
- en
license: cc-by-4.0
task_categories:
- text-generation
pretty_name: SWE-rebench-V2
tags:
- software-engineering
- code
- swe
- rl
---
# SWE-rebench-V2
[](https://github.com/PrimeIntellect-ai/research-environments/tree/main/environments/swe/swerebench_v2_v1)
Full re-upload of Nebius's
[SWE-rebench-V2](https://huggingface.co/datasets/nebius/SWE-rebench-V2)
([paper](https://arxiv.org/abs/2602.23866)): **32,076 / 32,079** freshly-mined GitHub PR tasks
across 17 languages. Unfiltered mirror for large-scale runs; the curated RL subsets are
[`SWE-rebench-V2-Filtered-Verified`](https://huggingface.co/datasets/PrimeIntellect/SWE-rebench-V2-Filtered-Verified)
and
[`SWE-rebench-V2-Filtered-Easy-Verified`](https://huggingface.co/datasets/PrimeIntellect/SWE-rebench-V2-Filtered-Easy-Verified).
## Changes vs upstream
* Dropped exactly 3 rows whose Docker Hub image no longer exists upstream (`dhi-mikeio` tags
`227-50037f2`, `442-3f8bb64`, `690-7882682` — manifests return `denied`; list ships as
`swe-rebench-v2-dead-upstream-images.json`). Nothing else is filtered.
License mirrors upstream: CC-BY-4.0.
## Splits
| Split | Rows |
|---|---:|
| `train` | 32,076 |
## How to use
Install the [`swerebench_v2_v1`](https://github.com/PrimeIntellect-ai/research-environments/tree/main/environments/swe/swerebench_v2_v1) taskset from
[research-environments](https://github.com/PrimeIntellect-ai/research-environments), then run it
end-to-end with [verifiers](https://github.com/PrimeIntellect-ai/verifiers):
```bash
uv pip install --prerelease=allow "git+https://github.com/PrimeIntellect-ai/research-environments.git#subdirectory=environments/swe/swerebench_v2_v1"
uv run eval --taskset.id swerebench_v2_v1 -m <your-model> -n 100 -r 4
```
## Generation
<details>
<summary>Reproduction script — <code>swe-rebench-v2.py</code></summary>
This dataset was created by running:
````bash
uv run datasets/swe-rebench-v2.py -H
````
````python
# swe-rebench-v2.py
"""Re-upload `nebius/SWE-rebench-V2` (32k) minus upstream-dead images.
Full mirror of the upstream train split with exactly one filter: a
manually-curated blocklist at ``swe-rebench-v2-dead-upstream-images.json``
(sibling of this file) drops the 3 rows whose Docker Hub image no longer
exists upstream (``dhi-mikeio`` tags 227-50037f2 / 442-3f8bb64 / 690-7882682 —
manifest requests return ``denied``, checked 2026-07-17). Every other row is
kept verbatim, including 68 rows whose images exist upstream but currently
fail Prime platform sandbox-image conversion — that failure is prime-side and
may be fixed, so those rows are not this dataset's problem to drop (the
curated RL subsets `SWE-rebench-V2-Filtered-Verified` / `-Filtered-Easy-Verified`
do exclude them).
``image_name`` is deliberately NOT rewritten to ``prime/primeintellect/...``
(unlike the filtered subsets): since the platform's 2026-07-15 org-less image
migration (ENG-4518), Docker Hub source refs like
``docker.io/swerebenchv2/<name>:<tag>`` resolve natively on Prime — and the
14k images imported after the migration exist in the registry *only* under
those source refs, so a wholesale rewrite would point them at nonexistent
names. Source refs are the one convention that covers every row on Prime,
Docker, and Modal runtimes alike.
Field source notes:
* `problem_statement` is the raw GitHub issue body.
* `pr_description` is the raw merged PR description.
"""
# /// script
# requires-python = ">=3.12"
# dependencies = ["datasets>=4.0.0", "jinja2"]
# ///
import argparse
import json
import sys
import time
from pathlib import Path
from typing import cast
from huggingface_hub import create_repo, upload_file, whoami
from datasets import Dataset, load_dataset
SOURCE_REPO = "nebius/SWE-rebench-V2"
_DEAD_IMAGES_PATH = Path(__file__).parent / "swe-rebench-v2-dead-upstream-images.json"
_DEAD_IMAGES = frozenset(json.loads(_DEAD_IMAGES_PATH.read_text()))
def _normalize_image(image_name: str) -> str:
# Dataset rows carry e.g. ``docker.io/swerebenchv2/foo-bar:tag``; the
# blocklist omits the ``docker.io/`` prefix. Strip it for comparison.
prefix = "docker.io/"
return image_name[len(prefix) :] if image_name.startswith(prefix) else image_name
def prepare_data() -> Dataset:
ds = cast(Dataset, load_dataset(SOURCE_REPO, split="train"))
return ds.filter(
lambda ex: _normalize_image(ex.get("image_name") or "") not in _DEAD_IMAGES,
num_proc=8,
load_from_cache_file=False,
)
def _swe_card(key: str):
"""Build this dataset's card from the shared SWE card registry (swe_cards.py)."""
sys.path.insert(0, str(Path(__file__).resolve().parent))
from swe_cards import build_card
return build_card(key)
def push_card_to_hub(repo_name: str, push_to_hub: bool):
card = _swe_card("swe-rebench-v2")
if push_to_hub:
print(f"Pushing card to `{repo_name}`")
card.push_to_hub(repo_name, repo_type="dataset")
print(f"✅ Pushed card to `{repo_name}` to HF Hub")
else:
print("ℹ️ Skipped pushing card to HF Hub. To push, use the `--push-to-hub` or `-H` flag.")
def main(repo_name: str, push_to_hub: bool, private: bool):
print(f"⚙️ Re-uploading {SOURCE_REPO} minus {len(_DEAD_IMAGES)} upstream-dead images")
start_time = time.time()
dataset = prepare_data()
elapsed = time.time() - start_time
print(f"✅ Kept {len(dataset):,} rows in {elapsed:.2f} seconds")
if push_to_hub:
create_repo(repo_name, private=private, repo_type="dataset", exist_ok=True)
push_card_to_hub(repo_name, push_to_hub)
dataset.push_to_hub(repo_name, private=private)
upload_file(
path_or_fileobj=str(_DEAD_IMAGES_PATH),
path_in_repo=_DEAD_IMAGES_PATH.name,
repo_id=repo_name,
repo_type="dataset",
)
print(f"✅ Pushed dataset to https://huggingface.co/datasets/{repo_name}")
def check_write_access(org: str):
is_authed = False
try:
info = whoami()
token = info["auth"]["accessToken"]["displayName"]
for entity in info["auth"]["accessToken"]["fineGrained"]["scoped"]:
if entity["entity"]["name"] == org and "repo.write" in entity["permissions"]:
is_authed = True
except Exception:
raise ValueError("❌ You are not logged in. Please run `hf auth login` or `export HF_TOKEN=...`")
if not is_authed:
raise ValueError(f"❌ Your current token `{token}` does not have write access to `{org}`")
print(f"✅ Confirmed write access with token `{token}` to `{org}`")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--username", "-U", default="PrimeIntellect", type=str, help="The username to push the dataset to."
)
parser.add_argument("--dataset-name", "-D", default="SWE-rebench-V2", type=str, help="The dataset name.")
parser.add_argument("--dataset-private", "-p", action="store_true", help="Whether to make the dataset private.")
parser.add_argument("--push-to-hub", "-H", action="store_true", help="Whether to push the dataset to the hub.")
args = parser.parse_args()
assert len(args.dataset_name.split("/")) == 1, "Dataset name must not include the username"
if args.push_to_hub:
check_write_access(args.username)
main(
repo_name=f"{args.username}/{args.dataset_name}",
push_to_hub=args.push_to_hub,
private=args.dataset_private,
)
````
</details>
## Original Dataset Card
Snapshot of the [`nebius/SWE-rebench-V2`](https://huggingface.co/datasets/nebius/SWE-rebench-V2)
card at card-build time — see the live card for updates.
<details>
<summary>Original <code>nebius/SWE-rebench-V2</code> dataset card</summary>
# SWE-rebench-V2
## Dataset Summary
SWE-rebench-V2 is a curated dataset of software-engineering tasks derived from real GitHub issues and pull requests. The dataset contains 32,079 samples covering Python, Go, TypeScript, JavaScript, Rust, Java, PHP, Kotlin, Julia, Elixir, Scala, Swift, Dart, C, C++, C#, R, Clojure, OCaml, and Lua.
For log parser functions, base Dockerfiles, and the prompts used, please see https://github.com/SWE-rebench/SWE-rebench-V2
The detailed technical report is available at [“SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale”](https://arxiv.org/abs/2602.23866).
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("nebius/SWE-rebench-V2", split="train")
print(len(ds)) # 32079
```
## Dataset Structure
| Field | Type | Description |
|---|---|---|
| `instance_id` | `string` | Unique identifier for the instance |
| `repo` | `string` | GitHub repository in `owner/repo` format |
| `base_commit` | `string` | Git commit SHA of the base before the fix |
| `patch` | `string` | The gold patch that resolves the issue |
| `test_patch` | `string` | Diff adding or modifying tests that verify the fix |
| `problem_statement` | `string` | Issue description the patch addresses |
| `pr_description` | `string` | Full pull request description |
| `created_at` | `int64` | Unix timestamp (milliseconds) of the issue/PR creation |
| `image_name` | `string` | Docker image name used for the evaluation environment |
| `language` | `string` | Primary programming language of the repository |
| `interface` | `string` | Description of the code interface changed by the patch |
| `license` | `string` | SPDX license identifier of the repository |
| `FAIL_TO_PASS` | `list[string]` | Test IDs that fail before the patch and pass after |
| `PASS_TO_PASS` | `list[string]` | Test IDs that pass both before and after the patch |
| `install_config` | `struct` | Configuration needed to reproduce the test environment |
| `meta` | `struct` | Metadata and LLM-generated quality annotations |
# License
The dataset is licensed under the Creative Commons Attribution 4.0 license. However, please respect the license of each specific repository on which a particular instance is based. To facilitate this, the license of each repository at the time of the commit is provided for every instance.
# Citation
```bibtex
@misc{badertdinov2026swerebenchv2languageagnosticswe,
title={SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale},
author={Ibragim Badertdinov and Maksim Nekrashevich and Anton Shevtsov and Alexander Golubev},
year={2026},
eprint={2602.23866},
archivePrefix={arXiv},
primaryClass={cs.SE},
url={https://arxiv.org/abs/2602.23866},
}
</details>
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