NVIDIA-Merlin/HugeCTR
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
This framework helps data scientists and machine learning practitioners quickly train and deploy recommendation models, specifically those used for predicting click-through rates. You feed in large datasets of user interactions and item information, and it outputs a highly efficient, GPU-accelerated model capable of making personalized recommendations. It's designed for anyone building and optimizing recommendation systems for online platforms.
1,051 stars.
Use this if you need to rapidly train and deploy very large-scale deep learning models for personalized recommendations or click-through rate prediction on GPU hardware.
Not ideal if you are working with small datasets or do not have access to GPU resources for training and inference.
Stars
1,051
Forks
204
Language
C++
License
Apache-2.0
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/NVIDIA-Merlin/HugeCTR"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
shenweichen/DeepCTR-Torch
【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.
shenweichen/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
UlionTse/mlgb
MLGB is a library that includes many models of CTR Prediction & Recommender System by TensorFlow...
cnkuangshi/LightCTR
Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate...
wzhe06/SparkCTR
CTR prediction model based on spark(LR, GBDT, DNN)