| { | |
| "entry_class": "model.BitSerialReducer", | |
| "output_base": 2, | |
| "framework": "pytorch", | |
| "model_description": "Compute-optimized NeuralHorner v8 inference wrapper using the original ~471K-parameter bidirectional two-layer GRU transition. Stores weights in bfloat16, thresholds logits directly, reuses static feature channels, and removes one redundant modular-reduction pass by streaming one original operand directly through the learned Horner multiply transition.", | |
| "training_description": "Uses the published TrickyRex/bitserial-modmul-v8 weights (MIT), warm-started and fine-tuned by its author on one-step modular transitions. This derivative changes checkpoint precision and the mathematically equivalent inference schedule; it does not retrain the learned transition." | |
| } | |