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REGISTRY
Publish and share your ML models and datasets
Registry is a curated central repository that stores and provides versioning, aliases, lineage tracking, and governance of models and datasets.
ML lifecycle management
Manage your ML models and datasets seamlessly through every stage of the lifecycle – from development to staging to production.
CI/CD
As the single source of truth for which models are in production, Registry provides the foundation for an effective CI/CD pipeline by identifying the right models to reproduce, retrain, evaluate, and deploy.
Reproducibility
A system of record offering easy access to machine learning artifacts and detailed lineage tracking allows you to rebuild any model and reproduce any task in the ML lifecycle.
Discoverability
Share models and datasets across the organization. ML practitioners from different teams can explore and use published artifacts in their own experiments and CI/CD pipelines.
Governance and access control
Safeguard models and datasets across multiple teams. Ensure that users have the right access to artifacts they need. No more, no less.
The Weights & Biases end-to-end AI developer platform
Weave
Traces
Debug agents and AI applications
Evaluations
Rigorous evaluations of agentic AI systems
Playground
Explore prompts and models
Agents
Observability tools for agentic systems
Guardrails
Block prompt attacks and harmful outputs
Monitors
Continuously improve in prod
Models
Experiments
Track and visualize your ML experiments
Sweeps
Optimize your hyperparameters
Tables
Visualize and explore your ML data
Core
Inference
Explore hosted, open-source LLMs
Registry
Publish and share your AI models and datasets
Artifacts
Version and manage your AI pipelines
Reports
Document and share your AI insights
SDK
Log AI experiments and artifacts at scale
Automations
Trigger workflows automatically
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
Registry
Publish and share your ML models and datasets
Automations
Trigger workflows automatically
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
SDK
Log ML experiments and artifacts at scale