A microframework on top of PyTorch with first-class citizen APIs for foundation model adaptation
The simplest way to train and run adapters on top of foundation models
Manifesto | Docs | Guides | Discussions | Discord
The current recommended way to install Refiners is from source using Rye:
git clone "[email protected]:finegrain-ai/refiners.git"
cd refiners
rye sync --all-features
Refiners comes with a MkDocs-based documentation website available at https://refine.rs. You will find there a quick start guide, a description of the key concepts, as well as in-depth foundation model adaptation guides.
If you're interested in understanding the diversity of use cases for foundation model adaptation (potentially beyond the specific adapters supported by Refiners), we suggest you take a look at these outstanding papers:
We took inspiration from these great projects:
@misc{the-finegrain-team-2023-refiners,
author = {Benjamin Trom and Pierre Chapuis and Cédric Deltheil},
title = {Refiners: The simplest way to train and run adapters on top of foundation models},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/finegrain-ai/refiners}}
}