recursive language models

We have hosted the application recursive language models in order to run this application in our online workstations with Wine or directly.

Quick description about recursive language models:

RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom agents, environments, policy networks, and reward structures while leveraging built-in dataset utilities, logging, and checkpointing for reproducible experiments. RLM also includes integration with popular simulation environments and benchmark suites, giving researchers a ready-made playground for algorithm comparison and performance tracking.

Features:

• Unified API for defining and running reinforcement learning agents
• Modular components for composable pipelines
• Integrations with benchmark environments and simulators
• Support for distributed and multi-GPU training
• Built-in logging, checkpointing, and evaluation tools
• Configurable reward, policy, and replay buffer abstractions

Programming Language: Python.
Categories: