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TensorFlow Community Models

This repository provides a curated list of the GitHub repositories with machine learning models and implementations powered by TensorFlow 2.

Note: Contributing companies or individuals are responsible for maintaining their repositories.

Computer Vision

Image Recognition

Model Paper Features Maintainer
DenseNet 169 Densely Connected Convolutional Networks • FP32 Inference Intel
Inception V3 Rethinking the Inception Architecture
for Computer Vision
• Int8 Inference
• FP32 Inference
Intel
Inception V4 Inception-v4, Inception-ResNet and the Impact
of Residual Connections on Learning
• Int8 Inference
• FP32 Inference
Intel
MobileNet V1 MobileNets: Efficient Convolutional Neural Networks
for Mobile Vision Applications
• Int8 Inference
• FP32 Inference
Intel
ResNet 101 Deep Residual Learning for Image Recognition • Int8 Inference
• FP32 Inference
Intel
ResNet 50 Deep Residual Learning for Image Recognition • Int8 Inference
• FP32 Inference
Intel
ResNet 50v1.5 Deep Residual Learning for Image Recognition • Int8 Inference
• FP32 Inference
• FP32 Training
Intel
EfficientNet v1 v2 EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks • Automatic mixed precision
• Horovod Multi-GPU training (NCCL)
• Multi-node training on a Pyxis/Enroot Slurm cluster
• XLA
NVIDIA

Object Detection

Model Paper Features Maintainer
R-FCN R-FCN: Object Detection
via Region-based Fully Convolutional Networks
• Int8 Inference
• FP32 Inference
Intel
SSD-MobileNet MobileNets: Efficient Convolutional Neural Networks
for Mobile Vision Applications
• Int8 Inference
• FP32 Inference
Intel
SSD-ResNet34 SSD: Single Shot MultiBox Detector • Int8 Inference
• FP32 Inference
• FP32 Training
Intel

Segmentation

Model Paper Features Maintainer
Mask R-CNN Mask R-CNN • Automatic Mixed Precision
• Multi-GPU training support with Horovod
• TensorRT
NVIDIA
U-Net Medical Image Segmentation U-Net: Convolutional Networks for Biomedical Image Segmentation • Automatic Mixed Precision
• Multi-GPU training support with Horovod
• TensorRT
NVIDIA

Natural Language Processing

Model Paper Features Maintainer
BERT BERT: Pre-training of Deep Bidirectional Transformers
for Language Understanding
• FP32 Inference
• FP32 Training
Intel
BERT BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding • Horovod Multi-GPU
• Multi-node with Horovod and Pyxis/Enroot Slurm cluster
• XLA
• Automatic mixed precision
• LAMB
NVIDIA
ELECTRA ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators • Automatic Mixed Precision
• Multi-GPU training support with Horovod
• Multi-node training on a Pyxis/Enroot Slurm cluster
NVIDIA
GNMT Google’s Neural Machine Translation System:
Bridging the Gap between Human and Machine Translation
• FP32 Inference Intel
Transformer-LT (Official) Attention Is All You Need • FP32 Inference Intel
Transformer-LT (MLPerf) Attention Is All You Need • FP32 Training Intel

Recommendation Systems

Model Paper Features Maintainer
Wide & Deep Wide & Deep Learning for Recommender Systems • FP32 Inference
• FP32 Training
Intel
Wide & Deep Wide & Deep Learning for Recommender Systems • Automatic mixed precision
• Multi-GPU training support with Horovod
• XLA
NVIDIA
DLRM Deep Learning Recommendation Model for Personalization and Recommendation Systems • Automatic Mixed Precision
• Hybrid-parallel multiGPU training using Horovod all2all
• Multinode training for Pyxis/Enroot Slurm clusters
• XLA
• Criteo dataset preprocessing with Spark on GPU
NVIDIA

Contributions

If you want to contribute, please review the contribution guidelines.