Glyph β€” trained LoRA adapters

Three LoRA adapters on Qwen2.5-Coder-3B for a seeded logographic agent-language:

  • speaker: English task β†’ glyph symbols
  • builder: glyph symbols β†’ Python code
  • translator: glyph symbols β†’ English

Results (seed=0): compositional decode 12/22, cold-model self-explanation 13/22, byte reduction 98.8% vs English agent-to-agent. Code + demo: https://github.com/robertkeus/glyph-ai

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