Neptune.ai is an experiment tracking tool designed for foundation models, offering capabilities to monitor and debug model internals without performance tradeoffs. It allows users to log thousands of per-layer metrics, including losses, gradients, and activations, visualizing them with no lag. Key features include:
- Scalable Tracking & Visualization: Log metrics across all layers and visualize them in seconds, supporting models with billions of parameters.
- Deep Debugging: Spot hidden issues before they derail training by monitoring across layers to detect vanishing or exploding gradients and loss convergence failures.
- Run Forking: Gain better visibility into training with many restarts and branches, testing multiple configs simultaneously and seeing lineage for forked experiments.
- Self-Hosted Deployment: Deploy Neptune on-premises or in a private cloud for enhanced security and control.
Neptune.ai is used by researchers and enterprises to maintain stable model training, reduce wasted GPU cycles, and ensure compliance with security standards.
