Weights & Biases is a machine learning (ML) platform for building models faster through experiment tracking, data set versioning, visualizing model performance and model management. It can be integrated with existing ML code to get live metrics, terminal logs and system statistics streamed to the dashboard for further analysis. Recently, Weights & Biases has expanded into LLM observability with Traces. Traces visualizes the execution flow of prompt chains as well as intermediate inputs/outputs and provides metadata around chain execution (such as tokens used and start and end time). Our teams find it useful for debugging and getting a greater understanding of the chain architecture.
Weights & Biases is a machine learning (ML) platform for building models faster through experiment tracking, data set versioning, visualizing model performance and model management. You can integrate it with existing ML code and quickly get live metrics, terminal logs and system statistics streamed to the dashboard for further analysis. Our teams have used Weights & Biases, and we like its collaborative approach to model building.
