Repository:volotat/mini-AGI
mini-AGI: Byte-Level Continual Learning on 8 GB VRAM Consumer Hardware
mini-AGI is an experimental open-source byte-level language model designed to demonstrate continual learning from a single stream of data (batch size 1) on modest 8 GB VRAM hardware. By paging model weights from disk into GPU memory as needed, it decouples parameter capacity from VRAM limits while dynamically scaling its architecture.
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