Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP

Face recognition system for ID photos

Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.

A PyTorch implementation of the 'FaceNet' paper for training a facial recognition model with Triplet Loss using the glint360k dataset. A pre-trained model using Triplet Loss is available for download.

Multi-threaded GUI manager for mass creation of AI-generated art with support for multiple GPUs.

Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python

multi-gpu pre-training in one machine for BERT without horovod (Data Parallelism)

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

GPU-ready Dockerfile to run Stability.AI stable-diffusion model v2 with a simple web interface. Includes multi-GPUs support.

Multi-GPU training for Keras

Chains stable-diffusion-webui instances together to facilitate faster image generation.

🎯 Gradient Accumulation for TensorFlow 2

testing multi gpu for pytorch

Neutron: A pytorch based implementation of Transformer and its variants.

XReflection is a neat toolbox tailored for single-image reflection removal(SIRR). We offer state-of-the-art SIRR solutions for training and inference, with a high-performance data pipeline, multi-GPU/TPU/NPU support, and more!

Benchmark for both NVIDIA and AMD GPU

Code repository for training multi-label classification models on the CheXpert Chest X-ray dataset.

Code repository for training a brain tumour U-Net 3D image segmentation model using the 'Task1 Brain Tumour' medical segmentation decathlon challenge dataset.

Multi-GPU version of BERT, implemented with Tensorflow 1.9