Translated🎭 277 plug-and-play AI expert roles — supporting 20 tools such as Claude Code/Cursor/Copilot, covering 20 departments including engineering/design/marketing/finance. Includes 64 original agents for the Chinese market (Xiaohongshu/Douyin/WeChat/Feishu/DingTalk/Qt host computer software/mechanical design). Paired with the orchestrator agency-orchestrator, a single sentence lets multiple experts collaborate automatically as a DAG.
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Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
Agent framework and applications built upon Qwen>=3.0, featuring Function Calling, MCP, Code Interpreter, RAG, Chrome extension, etc.
Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team.
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.
- chatbot
- chatgpt-api
- chatglm
- claude
Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.
TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")
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!
Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own
- decision-model
- jev
- qwen3
~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.
- academia
- arxiv
- brave
- deep-research
TranslatedQwen-Image 2.1 NSFW/pose image generation skill: author-level prompt recipes + NSFW LoRA + 136-pose VNCCS mannequin control; works with Claude Code / Codex / Cursor / OpenClaw
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
- interpretability
- mechanistic-interpretability
- qwen
- steering
TranslatedCurated agent skills for AI short drama, micro drama / microdrama, vertical drama and manju (AI comic drama): screenwriting, adaptation, storyboards, Seedance / Kling / MiniMax video prompts. Usable with agents such as Qwen (千问), Doubao (豆包), Lobster (龙虾) OpenClaw, WorkBuddy, Claude Code and Codex.
- agent-skills
- ai-short-drama
- awesome
- awesome-list
Local CLI Copilot, powered by Ollama. 💻🦙
GVS5H: Five Qwen3.8-27B Models Match Claude Fable 5 on LiveCodeBench Hard | Fable 5 Level Coding for a Fifth the Price - or on a Single GPU
The Open Source Strix Halo AI engine. Qwen 3.8 Flash Next Q4_K_XL: 1,801.01 pp, 73.17 tg single user, 194.37 tok/s 8 users; Qwen 3.8 27B Q4_K_XL: 656.33pp, 70.56tg tok/s single user with DFlash2
- amd
- llm
- strix-halo
- gfx1151
TranslatedVoice AI girlfriend for DeepSeek Harness: Whisper voice input + Qwen3-TTS voice cloning + sentence-level streaming read-aloud + digital human animation window. Two modes, interrupt and queue; speaking interrupts it.
- ai-girlfriend
- companion
- deepseek-harness
- digital-human
Implementing LLM architectures from scratch in PyTorch
- gemma3
- llama4
- llm
- moe
Run large AI models on your own PC: Qwen3.8-Flash-Next on Strata's engine, and GLM 5.3 Flash, DeepSeek V4 Flash, LFM2.5, Qwen3.6, Ornith 1.5, Gemma 4, Tiel Coder and MiniCPM-V on a second engine written for PolyStrata. One-click install for Windows and Linux, OpenAI/Anthropic API on localhost.
- anthropic-api
- cuda
- gemma
- gguf
llama.cpp on a jailbroken PS5: run any GGUF model natively on the console, starting with Qwen 3.8
Stop paying the multimodal tax. Your AI agent keeps every image it has seen but only sends the ones it needs: lighter chats, no endless reconnecting, no starting over. Works with Codex, Claude Code, Cline, Gemini CLI, OpenCode, WorkBuddy and more. Install once, forget it.
- codex
- codex-plugin
- context-management
- developer-tools
A computer, compiled into the weights of a language model. An exact CPU inside Qwen3.5-4B, with Gated DeltaNet state as RAM.