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Dedicated services that run training and model serving, supporting both local and remote execution.
Distinct from Platform as a Service: Distinct from Platform as a Service: focuses specifically on managed training and model serving for ML, not general application hosting.
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rllm is an asynchronous reinforcement learning framework for training language agents. It provides a unified pipeline that runs the same agent code for both evaluation and training, automatically capturing traces for gradient computation. The framework supports distributed reinforcement learning across multiple GPUs and nodes using pluggable backends, and executes agents in isolated sandboxes—either locally or in the cloud—for safe and scalable rollout collection. It trains agents built with LangGraph, SmolAgents, OpenAI Agents SDK, or custom frameworks without requiring core logic changes. T
Runs training and model serving through a dedicated service, supporting both local and remote execution.