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.
DeepTutor: Lifelong Personalized Tutoring. https://deeptutor.info/.
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
DSPy: The framework for programming—not prompting—language models
SGLang is a high-performance serving framework for large language models and multimodal models.
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
Open Source AI Platform - AI Chat with advanced features that works with every LLM
Code and documentation to train Stanford's Alpaca models, and generate the data.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
Train transformer language models with reinforcement learning.
The absolute trainer to light up AI agents.
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Topic Modelling for Humans
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
Retrieval and Retrieval-augmented LLMs
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
[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
Solve Visual Understanding with Reinforced VLMs