Argo, the ship that carried Jason and the Argonauts on their quest for the Golden Fleece

This is a playground to re-implement model architectures from industry/academic papers in Pytorch. The primary goal is educational and the target audience is for those who would like to start journey in machine learning & machine learning infra. The code implementation is optimized for readability and expandability, while not for the best of performance.

• data: functions for dataset management, such as downloading public dataset, cache management, etc
• model: model code implementation
• trainer: simple wrapper around train/val/eval loop
• server: simple inference stack for recommendation system

1. install the dependency pip install -r requirements.txt, pip install -e .
2. run python server/inference_engine.py to start the inference server, it would listen on 8000 port
3. run bash scripts/server_request.sh to send a dummy request

• Deep Interest Network for Click-Through Rate Prediction
• TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest
• Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
• Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations

• ✅ Deep Interest Network E2E training & inference example, MovieLen Small
• TransAct training & inference example, MovieLen Small
• MovieLen item embedding generation, collaborative filtering, two-towers, LLM
• HSTU training & inference example, MoiveLen Small
• Kuaishou Dataset
• Deep Interest Network Scaling, MovieLen 32M dataset
• RQ-VAE