Tiny hackable CUDA language model implementation
Summary
The article describes a compact CUDA-accelerated transformer that processes 8-bit tokens, trained to predict the next byte. It covers architecture details (byte-level embeddings, causal self-attention, swish activation), optimization with AdamW, BLAS usage for performance, and Ubuntu run steps. It positions the project as an open-source, self-contained example of a byte-based LLM.