Pinned Repositories
deep-learning-containers
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
sagemaker-inference-toolkit
Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
sagemaker-pytorch-inference-toolkit
Toolkit for allowing inference and serving with PyTorch on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
deep-learning-containers
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
sagemaker-pytorch-inference-toolkit
Toolkit for allowing inference and serving with PyTorch on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
serve
Serve, optimize and scale PyTorch models in production
serve
Serve, optimize and scale PyTorch models in production
server
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
chen3933's Repositories
chen3933/deep-learning-containers
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
chen3933/sagemaker-pytorch-inference-toolkit
Toolkit for allowing inference and serving with PyTorch on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
chen3933/serve
Serve, optimize and scale PyTorch models in production