mini-AGI trains and keeps learning on one 8GB GPU
mini-AGI is a toy-level byte language model that lets someone with an 8 GB VRAM GPU train from scratch and keep teaching it from a live data stream, instead of starting with a frozen model. It pages weights from disk, grows capacity when needed, and applies one gradient step per chunk it reads, using the same path for training and generation. The weights are not published yet, and the current run is still making its first pass through the corpus.