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Organization · Verified on Hugging Face

Nebius

nebius

AI-centric cloud platform ready for intensive workloads Training-ready platform with NVIDIA® H100 Tensor Core GPUs. Competitive pricing. Dedicated support.

Models in Library0
Datasets in Library2
Models on Hugging Face10
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Datasets

Dataset · Text generation

SWE-rebench-V2

Nebius

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”. 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…

Publicly accessible cc-by-4.0

Dataset · Other

SWE-rebench

Nebius

SWE-rebench is a large-scale dataset designed to support training and evaluation of LLM-based software engineering (SWE) agents, building upon and expanding our earlier release, SWE-bench-extra. It is constructed using a fully automated pipeline that continuously extracts real-world interactive SWE tasks from GitHub repositories at scale, as detailed in our paper SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents. The dataset currently comprises over 21,000 issue–pull request pairs from 3,400+ Python repositories, each validated for correctness through automated environment setup and test execution. A curated subset of these…

Publicly accessible cc-by-4.0