Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.
- fine-tuning
- llama
- llms
- gemma
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Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.
SGLang is a high-performance serving framework for large language models and multimodal models.
Train transformer language models with reinforcement learning.
The absolute trainer to light up AI agents.
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
Easily fine-tune (SFT/RL), evaluate, and deploy Qwen, Gemma, or any open agentic LLM/VLM!
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
Infrastructure for continually self‑improving agents
Solve Visual Understanding with Reinforced VLMs
Democratizing Reinforcement Learning for LLMs
The RL Bridge for LLM-based Agent Applications. Made Simple & Flexible.
RLinf: Reinforcement Learning Infrastructure for Embodied and Agentic AI
A Next-Generation Training Engine Built for Ultra-Large MoE Models
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
Translated"Large Language Models" (《大语言模型》), authors: Zhao Xin, Li Junyi, Zhou Kun, Tang Tianyi, Wen Jirong