airoboros

# airoboros: using large language models to fine-tune large language models

This is my take on implementing the [Self-Instruct paper](https://arxiv.org/abs/2212.10560).  The approach is quite heavily modified, and does not use any human-generated seeds.

This updated implementation supports either the /v1/completions endpoint or /v1/chat/completions, which is particularly useful in that it supports gpt-4 and gpt-3.5-turbo (which is 1/10 the cost of text-davinci-003).

Huge thank you to the folks over at [a16z](https://a16z.com/) for sponsoring the costs associated with building models and associated tools!

## Install

via pip:
```
pip install --no-build-isolation airoboros
```

from source (keeping the source):
```
git clone https://github.com/jondurbin/airoboros
pip install -e --no-build-isolation ./airoboros
```

## Key differences from self-instruct/alpaca

* support for either /v1/completions or /v1/chat/completions APIs (which allows gpt-3.5-turbo instead of text-davinci-003, as