Coldint (COLaborative Destributed INcentivized Training) advances collaborative, distributed model training and research with incentives for publishing improvements. Forked from subnet 9 pretraining, it addresses the lack of incentive for small incremental improvements. Initial competition rewards miners for improving model scores on the Fineweb-edu-2 dataset, with additional rewards for code contributions and key insights.
This subnet is currently safe from deregistration.
Yuma Pulse™
Distributed Training
Collaborative model training across decentralized miners with incentives aligned to publishing improvements
Fineweb-edu Dataset
Initial competition benchmarks models against Fineweb-edu-2, the high-quality educational web corpus
Code Contribution Rewards
Earn rewards not just for model improvements but also for bug fixes, code contributions, and key insights
Research Innovation
Incentivizes sharing innovative ideas about model structure, training methods, and evaluation approaches