Lists (7)
Stars
Universal model exchange and serialization format for decision tree forests
An interface library for RL post training with environments.
A Demo of Retrieval Augmented Generation with Amazon Titan, Bedrock, Kendra, and LangChain
Animated Transition between Node-link and Adjacency Matrix
AIPerf is a comprehensive benchmarking tool that measures the performance of generative AI models served by your preferred inference solution.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
The official repo of Continuous-Time Sequential Recommendation with State Space Models (Under review)
[RelKD'24] Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models
1st Place Team Crane: @aswinkumar1999 @rathull @kyolebu
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
Tile primitives for speedy kernels
Deploying a Multimodal Recommender System on Kubernetes featuring Cold Start handling, Bloom Filters, and Feature Caching.
Algorithm powering the For You feed on X
Contextual multi-armed bandit recommender system using Vowpal Wabbit
DeepSeek 4 Flash and PRO local inference engine for Metal, CUDA and ROCm
Rhino is a drop-in etcd v3 gRPC server that stores everything in a relational database.
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
Recommender System with Continuous Retraining on Amazon EKS with NVIDIA Merlin and Triton Inference Server
A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
High-performance GPU kernels for Ads and Recsys model training, independently implemented and optimized for real-world workloads and model-specific input characteristics.
Triton Model Navigator is an inference toolkit designed for optimizing and deploying Deep Learning models with a focus on NVIDIA GPUs.
Behavioral "black-box" testing for recommender systems
KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Examples demonstrating available options to program multiple GPUs in a single node or a cluster
An implementation of a deep learning recommendation model (DLRM)