AirLLM 70B inference with single 4GB GPU
A trilingual (繁中 / English / 简中) learning roadmap for agentic AI: from LLM basics to multi-agent systems, with 240+ curated resources and hands-on examples. 中文 AI agent 學習地圖。
Claude Code 的开源替代方案。Multi Agent AI 编程助手，CLI & Web UI 双入口。自托管，随处部署——手机浏览器也能完整操控。支持任意 LLM，原生浏览器自动化，90+ 命令。技能、插件与持久记忆。企业级安全，零锁定。Docker 一键部署。
Python toolkit for Chinese LLMs, with flexible batch capacity, structured real-time visulization and automated accumulation for streaming, and explicit feedback on vendor-native parameter validation.
A research fork of opencode demonstrating Language Anchoring — making LLMs think consistently in your language. Verified: 95%+ Chinese thinking compliance.
🔌 让 OpenAI Codex CLI 接入 GLM (智谱 AI) | Local proxy enabling Codex CLI to work with GLM models - 流式响应 & 工具调用 / Streaming & Tool Calling
re!think it. System prompt teaching LLMs to execute two core tasks: complex answers without hallucinations, and creative ideas without clichés. Written in math-like logic, which LLMs parse better than plain language. Built for mid-to-high complexity tasks, featuring a Bypass branch to execute simple prompts directly without added cognitive overhead
This repo introduces MagicData-CLAM, a Chinese SFT dataset, and provides to the community two relevant models that we finetuned. Contact business@magicdatatech.com for more information.
🦞 Curated OpenClaw config templates for Chinese LLM providers, multi-channel setups, automation & more | OpenClaw 配置模板大全
基于户晨风直播语料微调的 AI 对话模型
🎯 Fine-tuning LLMs using LlamaFactory for financial intent understanding | Evaluating open-source models on OpenFinData benchmark | Full implementation with multiple models (Qwen2.5/ChatGLM3/Baichuan2/Llama3)
Chinese Reasoning Language Model with Step-by-Step trajectories.
GhostAI 知识库 — 5 分钟拥有专属 AI 知识库 · DeepSeek + bge-m3 · 国内合规部署 · ¥39 起
✨ XingLing (星灵): A lightweight 0.68B Chinese Chat LLM built from scratch (Pretraining + SFT)
🚀 Optimize memory for large language models, enabling 70B models on a 4GB GPU and 405B Llama3.1 on 8GB VRAM without compression techniques.
0.1B 中文 Decoder-only LLM 端到端训练项目，覆盖 Tokenizer、Pretraining、SFT、GRPO、Benchmark 与 Inference，基于 PyTorch 从零实现模型、数据处理和训练评测流程。
Hands-on local LLM fine-tuning course (SFT / LoRA / PEFT / DPO / QLoRA) with a browser studio that visualizes loss, tensors, and adapter diffs.
Community-maintained multilingual resource hub for DeepSeek V4 — recipes, benchmarks, deployment, and migration guides in 7 languages
中文公司调研 Agent - 基于 guy-hartstein/company-research-agent (MIT) 的中文本地化版本
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