nvidia/Nemotron-SFT-SWE-v2
Dataset Description: Nemotron-SWE-v2 is a software engineering instruction tuning dataset designed to advance the capabilities of LLMs on SWE-Bench style tasks. It includes both agentic trajectories collected using the OpenHands framework and an agentless SWE subset for targeted sub-tasks such as code localization, code repair, and test generation. This dataset is ready for commercial use. Dataset Subsets: Nemotron-SWE-v2 contains the following subsets:… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-SWE-v2.
| Author / organization | nvidia |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 3.2K (as reported by Hugging Face) |
| Likes | 16 |
| Created | 8 March 2026 |
| Last updated at source | 11 March 2026 |
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Connected in the knowledge graph
- Luminia/MiniCPM5-1B-Agent-GGUFModel · used to train
- digi-texx/Qwen3.8-27B-FULL-NVFP4Model · used to train
Recent changes
- 17 Oct 2026 Description: Dataset Description: Nemotron-SWE-v2 is a software engineering instruction tuning dataset designed to advance the capabilities of LLMs on SWE-Bench style tasks. It includes both agentic trajectories collected using the OpenHands framework a → Dataset Description: Nemotron-SWE-v2 is a software engineering instruction tuning dataset designed to advance the capabilities of LLMs on SWE-Bench style tasks. It includes both agentic trajectories collected using the OpenHands framework a
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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.