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NovaSky-AI/SkyRL

SkyRL: A Modular Full-stack RL Library for LLMs observed · 2026-08-28

github.com/NovaSky-AI/SkyRL · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

80/100

  • Activity 99
  • Release rhythm 81
  • Longevity 35
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 52.0
  • age_days: 498
  • days_rel: 48
  • days_push: 9
  • n_releases_24m: 7

Full methodology

Adoption not part of the score

2201 stars · 410 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SkyRL is a modular full-stack reinforcement learning library for post-training large language models, combining a training framework (skyrl-train), a Tinker API-compatible backend (skyrl-tx), an agent layer for long-horizon tasks (skyrl-agent), and a Gymnasium-style environment library (skyrl-gym). It supports FSDP and Megatron training backends with vLLM inference on your own NVIDIA GPUs, including LoRA and full-parameter fine-tuning.

Use cases

  • train llm with reinforcement learning on my own gpus
  • run tinker api training scripts locally without code changes
  • fine-tune llm with grpo on gsm8k
  • build custom gym environments for rlhf training
  • train multi-turn tool-use agents with rl
  • rl post-training for sql and search agents
  • supervised fine-tuning of large language models with lora
  • train vision-language models with reinforcement learning

When to choose

  • you want to run RL post-training (GRPO, PPO, DAPO) for LLMs on your own NVIDIA hardware
  • you need Tinker API compatibility with zero code changes on local GPUs
  • you are training long-horizon, multi-turn tool-use agents
  • you want a modular RL stack with pluggable environments, trainers, and inference engines
  • you need to scale from 0.5B to 200B+ parameter models with FSDP or Megatron

When to avoid

  • you only need simple SFT without RL and prefer lightweight fine-tuning tools
  • you have no NVIDIA GPUs or CUDA 13.0-capable drivers
  • you want a fully managed hosted training service rather than self-managed infrastructure
  • you need RL for non-LLM domains like robotics control

Facets

library · maturity active

machine-learning llm-training agent-framework gpu-computing sdk large-language-models reinforcement-learning machine-learning gpu-computing python cloud reinforcement-learning rlhf grpo tinker-api fsdp megatron vllm ray lora post-training gymnasium-environments multi-turn-agents ai-agents gpu docker linux

10 sources

Member repositories

RepositoryRoleHealth v2
NovaSky-AI/SkyRLmain80

For agents

markdown · JSON · MCP: product_card(name="NovaSky-AI/SkyRL")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem