Kiln deeply integrates with the Git version control system to provide a complete data asset management and collaborative work solution for LLM development teams. The system brings all training data, model configurations, and fine-tuning results under version control, supporting specialized features such as branch management, diff comparison, and version rollback. Team members can complete all Git operations through a visual interface without having to memorize complex commands.
The technical implementation adopts distributed architecture design, and each data change records complete meta information (modifier, time, purpose, etc.). The unique dataset diff tool can visualize changes at the sample level and support accurate tracking of prompt engineering improvements, data enhancement adjustments, and other operations. The system automatically generates a version evolution map, which clearly shows the correlation between model performance and data iteration.
In the practice case of PingAn, a financial technology company, this feature helps its NLP team shorten the model update cycle from monthly to weekly, all data changes can be accurately traced back, and the collaboration efficiency is increased by 300%. The system also supports seamless docking with the enterprise's existing GitLab/GitHub repositories to realize the unified management of the R&D process.
This answer comes from the articleKiln: Simple LLM model fine-tuning and data synthesis tool, 0 code base to fine-tune your own small modelsThe
