🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
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🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
- deep-learning
- deep-learning-tutorial
- pytorch
- gan
A programming framework for agentic AI
aider is AI pair programming in your terminal
Curso para aprender el lenguaje de programación Python desde cero y para principiantes. 100 clases, 44 horas en vídeo, código, proyectos y grupo de chat. Fundamentos, frontend, backend, testing, IA...
A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent
A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
- agents
- flow-based-programming
- flow-engineering
- llm-agent
Romanian and Ukrainian child-safety structured-check toolkit and synthetic research records
An agent that compiles git maintenance chores into reusable programs, then decides whether to replay them by running checks rather than by guessing the task looks familiar
- agent-architecture
- git-automation
- llm-agents
- program-synthesis
The first exam for code agents in the physical world: frozen robot tasks from many benchmark suites, each answered with a program and verified in a separate sandbox. Runs on Harbor.
- ai-agents
- benchmark
- coding-agents
- embodied-ai
On-device Vision Model - a fully offline, free vision pipeline that gives text-only models (e.g. DeepSeek) image understanding and multilingual OCR through an OpenAI-compatible local API. Only tokens are needed: no API key, no subscription, no cloud cost. Recommended for native speakers of Chinese, English, Japanese and Korean.
Per-repo memory, outcome telemetry, and a calibrated-confidence gate for Claude Code, with MCP and AGENTS.md projections so other AI coding tools can read its context. Notes survive sessions; success claims need test evidence; your reverts are remembered. Local-only, stdlib runtime.