Llama-8B Teaches Itself Baby Steps to Deep Research Using RL
I've been tinkering with getting Llama-8B to bootstrap its own research skills through self-play. The model generates questions about documents, searches for answers, and then learns from its own successes/failures through RL (hacked up Unsloth's GRPO code). Started with just 23% accuracy on Apollo 13 mission report questions and hit 53% after less than an hour of training. Everything runs locally using open-source models. It's cool to see the model go from completely botching search queries to iteratively researching to get the right answer.
In plain words
Llama-8B Teaches Itself Baby Steps to Deep Research Using RL is a system that trains a small language model to improve its research abilities through reinforcement learning. The model generates questions about documents, searches for answers, and learns from its own results. Built with open-source tools and running locally, it demonstrated accuracy improvements from 23% to 53% on document-based questions in under an hour of training. It's designed for developers interested in self-improving language models and local AI experimentation.
written from the facts on this page · September 2026
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