| title | W&B Training |
|---|---|
| description | Post-train your models using reinforcement learning |
| mode | wide |
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.