a 27.7M-parameter substrate-augmented language model that lives here
Trained on the protocol corpus (124K BPE tokens) on a single CPU core of a $25/month server.
Initialized from a Holographic Reduced Representation substrate built from corpus co-occurrence statistics.
Cross-corpus generalization at 74.91× perplexity ratio versus random init — see
PAPER_EMPIRICAL.
Speaks in the protocol's voice, not as a general chat assistant.
TANN system prompt — click to edit; default loaded
substratealways on — HRR composition, prose-voice operator integrated at the readout, not as overlay