Datasets and models for instruction-tuning
txtinstruct is a framework for training instruction-tuned models.
The objective of this project is to support open data, open models and integration with your own data. One of the biggest problems today is the lack of licensing clarity with instruction-following datasets and large language models. txtinstruct makes it easy to build your own instruction-following datasets and use those datasets to train instructed-tuned models.
txtinstruct is built with Python 3.8+ and txtai.
The easiest way to install is via pip and PyPI
pip install txtinstruct
You can also install txtinstruct directly from GitHub. Using a Python Virtual Environment is recommended.
pip install git+https://github.com/neuml/txtinstruct
Python 3.8+ is supported
See this link to help resolve environment-specific install issues.
The following example notebooks show how to build models with txtinstruct.
| Notebook | Description | |
|---|---|---|
| Introducing txtinstruct | Build instruction-tuned datasets and models |  |