Jul 1, 2025 · Explore what GRPO is, how it works, the essential components needed for its implementation, and when it is most appropriate to use.

At it’s core, GRPO is a Reinforcement Learning (RL) algorithm that is aimed at improving the model’s reasoning ability. It was first introduced in their paper DeepSeekMath: Pushing the …

To understand how GRPO works, it can be broken down into four main steps: Generating completions, computing the advantage, estimating the KL divergence, and computing the loss.

Group Sampling (Grouped Rollouts): instead of evaluating one rollout per input, GRPO generates multiple completions (responses) from the current policy for each prompt. This set of …

Group Relative Policy Optimization (GRPO), a DeepSeek reinforcement learning method, is ideal when deep domain ex-pertise, precise style and tone control, specific output formatting, or …

Feb 5, 2024 · Second, we introduce Group Relative Policy Optimization (GRPO), a variant of Proximal Policy Optimization (PPO), that enhances mathematical reasoning abilities while …

Jan 31, 2025 · GRPO (Group Relative Policy Optimization) is a method used in reinforcement learning (RL) to help a model learn better by comparing different actions and making small, …

Feb 19, 2025 · A very simple GRPO implement for reproducing r1-like LLM thinking. This is a simple open source implementation that utilizes the core loss calculation formula referenced …

Beginner's Guide to transforming a model like Llama 3.1 (8B) into a reasoning model by using Unsloth and GRPO. DeepSeek developed GRPO (Group Relative Policy Optimization) to train …

In this notebook, we'll guide you through the process of post-training a Large Language Model (LLM) using Group Relative Policy Optimization (GRPO), a method introduced in the …