Find here DataChain and DVC news, findings, interesting reads, community takeaways, deep dive into machine learning workflows from data versioning and processing to model productionization.
Ensuring your machine learning models remain precise and efficient as time progresses, and verifying that your data consistently reflects the real-world scenario.
This post describes a production ML pipeline for fine-tuning large language models using DVC, SkyPilot, HuggingFace Transformers, and quantization techniques.
DVC 3.0 introduces a stack of tools outside the command line to bring it closer to
where you work (in code, IDE, web) while also focusing on DVC fundamentals.