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Platform
Models >
Experiments
Track and visualize your ML experiments
Sweeps
Optimize your hyperparameters
Tables
Visualize and explore your ML data
Reports
Visualize and explore your ML data
Training >
Serverless RL
Fine-tune LLMs without managing GPUs
ART
Open-source RL framework
Ruler
Automated reward function for RL
Inference >
OpenAI OSS
GPT OSS 20B, GPT OSS 120B
Alibaba Qwen3
23B A22B, 23B5B Thinking, Coder 480B
Meta Llama
Llama 4 Scout, 3.3 70B, 3.1 8B
MoonshotAI Kimi
Kimi K2
Microsoft Phi
Phi 4 Mini 3.8B
Hangzhou DeepSeek
DeepSeek V3.1, V3-0324, R1-0528
Z.ai
Z.AI GLM 4.5
Weave >
Traces
Explore and debug AI applications
Evaluations
Rigorous evaluations of AI applications
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Agents
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Guardrails
Block prompt attacks and harmful outputs
Monitors
Continuously improve in production
Core
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Artifacts
Version and manage your ML pipelines
SDK
Log ML experiments and artifacts at scale
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Trigger workflows automatically
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Microsoft
Learn how Microsoft uses W&B for their ML projects
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OpenAI
Learn how OpenAI Robotics uses W&B for large scale ML
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Announcing Serverless RL: Train agents without worrying about infra or GPUs
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