freerec 0.7.3

PyTorch library for recommender systems

FreeRec is a repository designed for easy (recommendation) data pre-processing and model training. I am a beginner in the field of recommender systems, so much of FreeRec's designs may not be as effective. In addition, you are free to specify your own framework based on FreeRec.

Requirements:

Python >= 3.9 | PyTorch | TorchData | PyG

conda create --name=FreeRec python=3.9
conda activate FreeRec

Note: After PyTorch 2.0, TorchData seems to have stopped being updated, and you can install it with --no-deps to avoid installing dependencies.

pip install --no-deps torchdata

Installation

pip install freerec

or (for latest)

pip install git+https://github.com/MTandHJ/freerec.git

Data Pipeline

Note: To make dataset, please download corresponding Atomic files from [RecBole]. Then, run freerec make --help.

Training Flow

Reference Code

• TorchRec: https://github.com/pytorch/torchrec
• DeepCTR-Torch: https://github.com/shenweichen/DeepCTR-Torch
• FuxiCTR: https://github.com/xue-pai/FuxiCTR
• BARS: https://github.com/openbenchmark/BARS
• RecBole: https://github.com/RUCAIBox/RecBole

Acknowledgements

Thanks to ChatGPT for the annotation of some code. For this reason, some of the comments may be illogical.