Last Updated: April 18th, 2021 (aitextgen v0.5.0)
A robust Python tool for text-based AI training and generation using OpenAI's GPT-2 and EleutherAI's GPT Neo/GPT-3 architecture.
aitextgen is a Python package that leverages PyTorch, Hugging Face Transformers and pytorch-lightning with specific optimizations for text generation using GPT-2, plus many added features. It is the successor to textgenrnn and gpt-2-simple, taking the best of both packages:
- Finetunes on a pretrained 124M/355M/774M GPT-2 model from OpenAI or a 125M/355M GPT Neo model from EleutherAI...or create your own GPT-2/GPT Neo model + tokenizer and train from scratch!
- Generates text faster than gpt-2-simple and with better memory efficiency!
- With Transformers, aitextgen preserves compatibility with the base package, allowing you to use the model for other NLP tasks, download custom GPT-2 models from the HuggingFace model repository, and upload your own models! Also, it uses the included
generate()function to allow a massive amount of control over the generated text.
- With pytorch-lightning, aitextgen trains models not just on CPUs and GPUs, but also multiple GPUs and (eventually) TPUs! It also includes a pretty training progress bar, with the ability to add optional loggers.
- The input dataset is its own object, allowing you to not only easily encode megabytes of data in seconds, cache, and compress it on a local computer before transporting to a remote server, but you are able to merge datasets without biasing the resulting dataset, or cross-train on multiple datasets to create blended output.
aitextgen can be installed from PyPI:
pip3 install aitextgen
For more info on how to use aitextgen, check out the nav sidebar, or you can do a Hello World tutorial.