Prerequisites
Set up your environment to use W&B Training.
W&B Training
Post-train your models using reinforcement learning.
less than a minute
Now in public preview, W&B Training offers serverless reinforcement learning (RL) for post-training large language models (LLMs) to improve their reliability performing multi-turn, agentic tasks while also increasing speed and reducing costs. RL is a training technique where models learn to improve their behavior through feedback on their outputs.
W&B Training includes integration with:
- ART, a flexible RL fine-tuning framework.
- RULER, a universal verifier.
- A fully-managed backend on CoreWeave Cloud.
To get started, satisfy the prerequisites to start using the service and then see OpenPipe’s Serverless RL quickstart to learn how to post-train your models.
Serverless RL
Learn about how to more efficiently post-train your models using reinforcement learning.
API Reference
Complete API documentation for W&B Training.
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