fmcore is a specialized toolkit for scaling experimental research with Foundation Models. Our utilities for inference, tuning, and evaluation handle billion-scale models and datasets, letting you skip the boilerplate and focus on pushing AI research forward. Developed by researchers, for researchers, fmcore offers a robust, flexible platform that streamlines your workflow without sacrificing rigor.
We recommend installing dependencies in a new Anaconda environment using the commands below.
These commands were tested to work on Deep Learning AMI GPU PyTorch 1.13.1 (Amazon Linux 2) 20230221 on AWS.
Install dependencies:
conda create -n fmcore python=3.11.8 --yes
conda activate fmcore
pip install uv ## Speed up installation
uv pip install -r requirements.txt
uv pip install "spacy==3.7.4" "spacy-transformers==1.3.5"
uv pip install "setuptools==69.5.1"
Certain features need additional steps, e.g.
python -m spacy download en_core_web_lg
python -c "import nltk; nltk.download('punkt');"
See CONTRIBUTING for more information.
This project is licensed under the Apache-2.0 License.
