• Picks
  • Discover
  • Alternatives
  • About

© 2026 Willet

  • Newsletter
  • About
  • FAQ
  • Terms
  • Privacy & Cookies
Join the Discord (opens in a new tab)
RadixArk avatar

Miles

Reinforcement learning framework for post-training large language models

  • AI models and runtimes
View on GitHub
Website

Featured by Willet

What it is

Miles is a Python framework for RL post-training of LLMs and vision-language models, pairing SGLang for rollout generation with Megatron-LM, FSDP2, or torchtitan for training. It supports fully asynchronous rollout and training, fast in-loop weight updates, low-precision training such as FP8 and NVFP4, LoRA, and fault recovery when inference engines fail. ML engineering teams use it to run GRPO, PPO, SFT, and on-policy distillation on large MoE models across NVIDIA and AMD GPU clusters, including training coding and computer-use agents in sandboxed environments.

Images

Facts

Stars
3.2k3,174

Forks
566
Commits
2,960
Contributors
129
Language
Python
License
Apache-2.0
Last commit
Oct 20, 2026
On GitHub since
October 2025
First release
August 2026
Platforms
Linux, library
Self-hostable
No
Tags
  • model-training
  • reinforcement-learning
  • machine-learning
  • gpu-computing
  • fine-tuning

Last synced from GitHub on Oct 20, 2026

Share and more

Comments

No comments yet. Start the conversation.

The 10 best overlooked open-source projects, every Monday.

Similar projects

  • THUKEG avatar

    slime

    Reinforcement learning post-training framework for large language models

    8.7k
  • AReaL Project avatar

    AReaL

    Asynchronous reinforcement learning system for training LLM agents

    5.9k
  • Microsoft avatar

    Agent Lightning

    Reinforcement learning framework for training LLM agents in real harnesses

    18.8k