Case Study: Open Climate Fix improves solar forecasting with Weights & Biases

Open Climate Fix Improves Solar Forecasting With Weights & Biases

Open Climate Fix, a London-based non-profit R&D lab, works to improve solar forecasting with machine learning to help reduce carbon emissions. As a small team with distributed expertise, they needed a flexible way to manage experiments, improve collaboration, and automate key parts of their ML workflow using Weights & Biases.

With Weights & Biases, Open Climate Fix centralized experiment tracking, model and dataset visibility, and workflow documentation in a single system of record. The platform integrated with their HuggingFace-hosted models to provide full training logs, traceability, and reproducibility, helping the team debug faster, collaborate more effectively, and build models with greater speed and transparency.

Open Climate Fix

Jacob Bieker

Senior Machine Learning Research Engineer