Tag: lfm3

A Neuron Atlas for a Speech Model: What a Local 4B Can Label, What Replays Bit for Bit, and the Voice Levers We Had to Re-check

A one-day feasibility probe on LFM3-Audio-2B, a 2B speech-to-speech model: a local 4B model wrote labels for 300 of its 184,320 MLP neurons, a simulator scored them against a shuffled baseline, steering checked whether they are causal, and every test replayed bit for bit in new processes and across Metal and CUDA. Labels work for selective neurons only, families built from descriptions do not, labels transfer to a text model with another tokenizer, and of the voice neurons we first reported, three survived a 16-seed rerun against random neurons.