| ---
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| license: mit
|
| tags:
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| - from-scratch
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| - opcode
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| - ternary
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| - trit
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| - execution-verified
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| - tiny
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| - superseded
|
| ---
|
| <!-- scbe-status -->
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| > **Status: superseded.** Canonical coding model: [scbe-coding-agent-vtc-qwen15-v1-gguf](https://hf.co/issdandavis/scbe-coding-agent-vtc-qwen15-v1-gguf). Kept as research history.
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|
|
| # Binary-Trit Coder (Clay's opcode model)
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|
|
| A **from-scratch, 3.17M-param causal transformer** trained from *random init* on Issac's own opcode
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| substrate β a bijective ternary ("trit") op grammar: `join (+)`, `take (β)`, `weave (Γ)` over digit leaves,
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| prefix-notation, depth-2. No pretraining, no outside corpus.
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|
|
| ## Honest benchmark β its OWN domain, not Python
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| The metric is **execution-verify rate**: sample a program, *run it for real*, check the model's answer.
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| | Test | Score |
|
| |---|---|
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| | in-distribution (depth-2, fresh) | **98.6%** |
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| | OOD generalization (depth-3, never trained) | 47.0% |
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|
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| **This is NOT a Python code-gen model.** It has an 18-token opcode vocab; it will score ~0 on
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| LiveCodeBench/SciCode (wrong domain). Its "learn from doing" signal is the verify-rate above.
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|
|
| ## The chrysalis (capability layers, all execution-verified)
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| - variables/let-bindings (69.5% end-to-end; 100% with a calculator + show-work)
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| - ping-pong Ο-lattice solver β recovers a hidden intermediate 100%
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| - calc-offload, dark-space inference, combustion candidate-spark
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|
|
| ## Files
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| `scratch_coder.pt` (weights + vocab), `config.json`. Architecture + inference in
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| [github.com/issdandavis/loom](https://github.com/issdandavis/loom) `scratch_coder.py`.
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|
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| *Thesis: coding is finite + bijective + execution-verifiable, so a small model from random init can MASTER
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| the mapping β proven here at 98.6%.*
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|
|
