nanogpt-experiments/README.md

nanoGPT

The cleanest, fastest repository for training/finetuning medium-sized GPTs.

This repo currently requires reading the code, but it's not that bad. work ongoing...

Getting started:

We need a few dependencies:

• pytorch, of course
• numpy
• pip install datasets for huggingface datasets
• pip install tiktoken for OpenAI's fast bpe code
• pip install wandb for optional logging

Then we want to render the detaset:

$ cd data/openwebtext
$ python prepare.py

To download and tokenize the openwebtext dataset. It will create a train.bin and val.bin which holds the GPT2 BPE token ids in a massive sequence. Then we're ready to kick off training. The training script currently tries to reproduce the smallest GPT-2 released by OpenAI, i.e. the 124M version of GPT-2. We can run it like so:

$ python train.py

Once some checkpoints are written to the output directory out, we're ready to sample from the model:

$ python sample.py