Model Registry

ML model registry and lifecycle management

OpenAI uses W&B Models to track all their model versions across 2000+ projects, millions of experiments, and hundreds of team members.

RBC needs governance to manage handoffs between research and compliance teams. W&B Models makes each stage transparent.

M-KOPA builds trust internally and with external auditors by leaning on the model registry’s full lineage tracking and audit trails. 

Collaborate centrally

With the whole team on the same page, you can iterate on models faster. Weights & Biases’ ML model registry gives you a central source of truth: it’s clear what model is in production and how new candidate models compare.

Governance at scale

Gain visibility into the model development process with just a few lines of code. Easily view model lineage and answer questions like, “What was the exact version of the dataset this model trained on?”

Model CI/CD

Automatically retrain and re-evaluate machine learning models to keep your team’s production fresh. Easily audit the history of updates, and avoid repeated manual steps for updating models.

ML model lifecycle

Centrally manage all your model versions through every lifecycle stage, from development to staging to production.

Model cards & QA

Visualize comparisons between model versions to evaluate performance. Identify regressions before deploying models to production.

Adopt ML model management best practices with W&B Models today.

The Weights & Biases platform helps you streamline your workflow from end to end

Models

Experiments

Track and visualize your ML experiments

Sweeps

Optimize your hyperparameters

Model Registry

Register and manage your ML models

Automations

Trigger workflows automatically

Launch

Package and run your ML workflow jobs

Weave

Traces

Explore and
debug LLMs

Evaluations

Rigorous evaluations of GenAI applications

Core

Artifacts

Version and manage your ML pipelines

Tables

Visualize and explore your ML data

Reports

Document and share your ML insights