What are the key points?

NanoEuler is a GPT-2 scale LLM built from scratch in C and CUDA. The project includes custom backpropagation, BPE tokenizer, and FlashAttention implementations. The codebase supports full pretraining and Supervised Fine-Tuning workflows for language models.

NanoEuler: GPT-2 Scale LLM Built in C/CUDA

•NanoEuler is a GPT-2 scale LLM built from scratch in C and CUDA.
•The project includes custom backpropagation, BPE tokenizer, and FlashAttention implementations.
•The codebase supports full pretraining and Supervised Fine-Tuning workflows for language models.

NanoEuler is a GPT-2 style large language model developed from scratch using pure C and CUDA. The project includes hand-written backpropagation, a BPE tokenizer (method for breaking text into subword units), and FlashAttention (algorithm to speed up transformer attention mechanisms). The implementation features full pretraining capabilities as well as Supervised Fine-Tuning (SFT). The repository is publicly hosted on GitHub by user JustVugg for community review and use.