HarryR/z80ai

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1117 stars · 50 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Z80-μLM is a 2-bit quantized micro language model designed to run on 8-bit Z80 processors with only 64KB of RAM, exportable as ~40KB CP/M .COM binaries or ZX Spectrum .TAP files. It includes Python training tools with quantization-aware training and pre-built examples like a chatbot and a 20 Questions game.

Use cases

• run a tiny language model on a vintage Z80 computer
• train a conversational chatbot in Python and export it as a CP/M .COM binary
• build a 20 Questions game for retro hardware
• experiment with extreme 2-bit weight quantization
• deploy a self-contained chatbot with no floating point on 64KB RAM
• generate training data for tiny models using Ollama or Claude API
• run a chatbot on a ZX Spectrum emulator

When to choose

• you want to run a language model on retro Z80 hardware or emulators like CP/M or ZX Spectrum
• you need an extremely small, self-hosted chatbot binary with integer-only inference
• you want to learn quantization-aware training and tiny ML techniques
• you enjoy retrocomputing projects with a fun, personality-driven twist

When to avoid

• you need a capable, production-quality language model or assistant
• you require modern NLP features like large context windows or fluent generation
• you need a licensed, well-supported library for commercial use (no license is specified)
• your target platform is not Z80-based

Facets

library · maturity active

machine-learning llm-inference chatbot serialization machine-learning chatbots embedded-systems python cross-platform tinyml retrocomputing z80 cpm 2-bit-quantization quantization-aware-training code-golf zx-spectrum vintage-computing quantization natural-language-processing

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