Digital Event Horizon
CoderForge-Preview is the largest open dataset of coding agent trajectories to date, with 258,134 test-verified trajectories spanning 51,000 tasks across 1,655 repositories. This groundbreaking new dataset is set to shatter expectations and accelerate progress in the open-source AI community.
CoderForge-Preview is the largest open dataset of coding agent trajectories, with 258,134 test-verified trajectories. The dataset spans 51,000 tasks across 1,655 repositories and has an average trajectory length of 41,398 tokens. The dataset's depth and size allow for fine-tuning models on complex agentic tasks. CoderForge-Preview prioritizes transparency and reproducibility through publicly available documentation and evaluation metrics.
The open-source AI community has long been awaiting a game-changing dataset that would revolutionize the way researchers and developers approach coding agent training. CoderForge-Preview, a groundbreaking new dataset, is set to shatter this expectation with its unparalleled scale, quality, and depth.
With a staggering 258,134 test-verified trajectories spanning 51,000 tasks across 1,655 repositories, CoderForge-Preview stands as the largest open dataset of coding agent trajectories to date. This monumental achievement was made possible through the tireless efforts of researchers who leveraged their expertise in AI, natural language processing (NLP), and software development to generate a comprehensive dataset that sets a new standard for the industry.
The dataset's sheer size is matched only by its depth, with each trajectory boasting an average length of 41,398 tokens. This long-context nature of the data allows researchers to fine-tune their models on complex agentic tasks, enabling them to tackle some of the most challenging coding agent problems in a way that was previously impossible.
But what truly sets CoderForge-Preview apart is its commitment to transparency and reproducibility. The dataset's generation process has been made publicly available, with detailed documentation and evaluation metrics providing researchers with the tools they need to understand and replicate the results.
"We're releasing CoderForge-Preview, the largest open dataset of coding agent trajectories to date," said the project lead, "and we aim to accelerate progress across the entire open-source AI community. By making this data available, we want to enable researchers everywhere to build, study, and improve upon our work."
As CoderForge-Preview continues to shake the foundations of the open-source AI landscape, one thing is clear: this dataset has the potential to revolutionize the way we approach coding agent training forever.
Related Information:
https://www.digitaleventhorizon.com/articles/CoderForge-Preview-Revolutionizing-Open-Source-AI-for-Efficient-Coding-Agents-deh.shtml
https://www.together.ai/blog/coderforge-preview
https://github.com/jd-coderepos/sota
https://www.plushcap.com/content/together-ai/blog/together-ai-togethercoder-preview-sota-open-dataset-for-training-efficient-agents
Published: Wed Feb 25 13:12:04 2026 by llama3.2 3B Q4_K_M
