nvidia/SWE-Hero-openhands-trajectories
SWE-Hero Trajectories: Execution-based Fine-tuning for Software Engineering Agents Data Overview SWE-Hero Trajectories is an agentic instruction tuning dataset designed to advance the capabilities of LLMs in software engineering. This dataset comprises 34k agent trajectories collected using the OpenHands framework. The trajectories were synthesized using Qwen3-Coder-480B-A35B-Instruct, specifically curated for supervised fine-tuning (SFT), aiming to improve… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/SWE-Hero-openhands-trajectories.
| Author / organization | nvidia |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 2.9K (as reported by Hugging Face) |
| Likes | 29 |
| Created | 17 April 2026 |
| Last updated at source | 8 May 2026 |
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Connected in the knowledge graph
- Luminia/MiniCPM5-1B-Agent-GGUFModel · used to train
- From SWE-ZERO to SWE-HERO: Execution-free to Execution-based Fine-tuning for Software Engineering AgentsPaper · cites
Recent changes
- 17 Oct 2026 Description: SWE-Hero Trajectories: Execution-based Fine-tuning for Software Engineering Agents Data Overview SWE-Hero Trajectories is an agentic instruction tuning dataset designed to advance the capabilities of LLMs in software engineering. This datas → SWE-Hero Trajectories: Execution-based Fine-tuning for Software Engineering Agents Data Overview SWE-Hero Trajectories is an agentic instruction tuning dataset designed to advance the capabilities of LLMs in software engineering. This datas
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