GitHub - karpathy/nanoGPT: The simplest, fastest repository for training/finetuning medium-sized GPTs.

🚀 Introducing karpathy/nanoGPT: a simple yet powerful tool for training medium-sized GPTs! 🤖✨ Perfect for quick model finetuning and text generation. Check out the easy setup and diverse features to level up your AI projects! #AI #GPT #GitHub

karpathy/nanoGPT is a repository for training/finetuning medium-sized GPTs, rewritten from minGPT.
The code is simple and hackable, focusing on teeth over education.
It can reproduce GPT-2 (124M) on OpenWebText in about 4 days of training.
Dependencies include pytorch, numpy, transformers, datasets, tiktoken, wandb, and tqdm.
It provides quick start instructions for training a character-level GPT on Shakespeare's works.
Different configurations are suggested based on available computational resources (CPU/GPU).
For reproducing GPT-2 results, preparation of OpenWebText dataset and distributed training setup are outlined.
Various OpenAI GPT-2 baseline models are evaluated on OpenWebText dataset.
Finetuning from a pretrained model is explained, allowing for quick adaptation to new text data.
Sampling/inference scripts are provided for pre-trained models or models trained by the user.
Efficiency notes include benchmarking and profiling with a bench.py script.
Future research directions and troubleshooting tips are suggested.
The repository acknowledgements include the mention of Lambda labs as the Cloud GPU provider.