For AI agents: a documentation index is available at the root level at /llms.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
LogoLogoNeMo Gym
DocumentationAPI Reference
DocumentationAPI Reference
  • About
    • Concepts
    • Architecture
    • Ecosystem
    • Release Notes
  • Get Started
    • Prerequisites
    • Installation
    • Quickstart
  • Agent Server
  • Model Server
    • vLLM
  • Resources Server
  • Data
    • Prepare and Validate
    • Download from Hugging Face
    • Prompt Config
  • Environment Tutorials
    • Single-Step Environment
    • Multi-Step Environment
    • Stateful Environment
    • Real-World Environment
    • Integrate external libraries
    • Add a benchmark
    • Verification Patterns
    • Aggregate Metrics
  • Training Tutorials
    • NeMo RL
    • Unsloth
    • Multi-Environment Training
    • Training with VeRL
    • Offline Training (SFT/DPO)
  • Model Recipes
    • Nemotron 3 Nano
    • Nemotron 3 Super
  • Infrastructure
    • Deployment Topology
    • Engineering Notes
  • Reference
    • Configuration
    • RL Framework Compatibility
    • CLI Commands
    • FAQ
  • Troubleshooting
    • Configuration Errors
  • Contribute
    • Development Setup
    • Environments
    • Integrate RL Frameworks
  • About
  • Concepts
  • Environments
  • Evaluation
  • Training
  • Key Terminology
  • Architecture
  • Ecosystem
  • Release Notes
  • Prerequisites
  • Installation
  • Quickstart
  • Agent Server
  • Model Server
  • vLLM
  • Resources Server
  • Data
  • Prepare and Validate
  • Download from Hugging Face
  • Prompt Config
  • Environment Tutorials
  • Single-Step Environment
  • Multi-Step Environment
  • Stateful Environment
  • Real-World Environment
  • Generating Training Data
  • Resources Server Implementation
  • Integrate external libraries
  • Add a benchmark
  • Verification Patterns
  • LLM-as-Judge
  • Aggregate Metrics
  • Training Tutorials
  • NeMo RL
  • About Workplace Assistant
  • Gym Configuration
  • Multi-Node Training
  • NeMo RL Configuration
  • Setup
  • Single Node Training
  • Unsloth
  • Multi-Environment Training
  • Training with VeRL
  • Offline Training (SFT/DPO)
  • Model Recipes
  • Nemotron 3 Nano
  • Nemotron 3 Super
  • Infrastructure
  • Deployment Topology
  • Engineering Notes
  • aiohttp vs httpx
  • Responses API
  • SWE RL Case Study
  • System Design
  • Reference
  • Configuration
  • RL Framework Compatibility
  • CLI Commands
  • FAQ
  • Troubleshooting
  • Configuration Errors
  • Contribute
  • Development Setup
  • Environments
  • New Environment
  • Integrate RL Frameworks
  • Generation Backend
  • Integration Footprint
  • On-Policy Corrections
  • Success Criteria
On this page
  • RL (GRPO)
  • Multi-Environment Training
  • SFT & DPO

Training Tutorials

||View as Markdown|

We have hands-on tutorials with supported training frameworks to help you train with NeMo Gym environments. If you’re interested in integrating another training framework, see the Training Framework Integration Guide.

See Training for a refresher on when to use GRPO, SFT, or DPO.

RL (GRPO)

NeMo RL

Tutorial-series: GRPO training to improve multi-step tool calling on the Workplace Assistant environment, scaling from single-node to multi-node training.

nemo rlgrpo3-5 hours
Unsloth

Example GRPO training on instruction following and reasoning environments.

unslothsingle-gpu30 min
VeRL

Example DAPO training on math and agentic environments using VeRL, with single and multi-environment support.

verldapomulti-node1 hour

Multi-Environment Training

Multi-Environment Training

Run multiple training environments simultaneously for rollout collection.

multi-environmentmulti-verifier

SFT & DPO

Offline Training with Rollouts

Transform rollouts into training data for supervised fine-tuning (SFT) and direct preference optimization (DPO).

sftdpo
Previous

Aggregate Metrics

Next

NeMo RL

NVIDIANVIDIA
Developer-friendly docs for your API
Privacy Policy | Your Privacy Choices | Terms of Service | Accessibility | Corporate Policies | Product Security | Contact

Copyright © 2026, NVIDIA Corporation.