MinRL provides clean, minimal implementations of fundamental reinforcement learning algorithms in a customizable GridWorld environment. The project focuses on educational clarity and implementation simplicity while maintaining production-quality code standards.

A (somewhat) minimal library for finetuning language models with PPO on human feedback.

Stop forcing LLMs to answer in one pass. Give them a runtime. Recursive Language Model that improves any LLM, while reducing token usage up to 4X.

Minimal RLHF implementation built on top of minGPT.

serverless url shortener built on top of cloudflare stack

Educational implementation of RL for LLMs in Pytorch

RL algorithms, minimal

Automatically exported from code.google.com/p/minrlz

Task for a JetBrains Internship 2017 application: RLE compression library port from C to Rust

A minimal PyTorch re-implementation of RLHF

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Sensor Logger

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