Liu MCP Server

What is Liu?

Liu is a general‑purpose, flexible and easy‑to‑use framework for reinforcement fine‑tuning (RFT) of large language models. It supports diverse application scenarios and serves as a unified platform for exploring advanced RL paradigms, with capabilities for synchronous/asynchronous, on‑policy/off‑policy, and online/offline training.

How to use Liu?

Install Liu via pip install trinity-rft==0.2.1 or from source (Python ≥3.10, CUDA ≥12.4, at least 2 GPUs required). Prepare a model and dataset from Huggingface or ModelScope, then launch a web interface with trinity studio --port 8080 to configure and run the RFT process, or use trinity run --config <config_path> on the command line after starting a Ray cluster.

Key features of Liu

• Unified RFT core supporting multiple training modes.
• First‑class agent‑environment interaction handling.
• Optimized data pipelines with active management.
• Modular, decoupled architecture for easy adoption.
• Web‑based graphical interfaces for low‑code usage.

Use cases of Liu

• Adapting LLMs to new multi‑turn or multi‑step agentic scenarios.
• Developing custom RL algorithms with plug‑and‑play classes.
• Low‑code monitoring and tracking of the learning process.
• Fine‑tuning models on reasoning tasks (e.g., GSM8k with GRPO).
• Running offline learning via DPO or SFT.