nikhil-sk

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-benchmarks

Benchmark scripts on SageMaker for various frameworks

nikhil-sk/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.

nikhil-sk/amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

nikhil-sk/backend

Common source, scripts and utilities for creating Triton backends.

nikhil-sk/checksum_repository_agent

The Triton repository agent that verifies model checksums.

nikhil-sk/common

Common source, scripts and utilities shared across all Triton repositories.

nikhil-sk/core

The core library and APIs implementing the Triton Inference Server.

nikhil-sk/dali_backend

The Triton backend that allows running GPU-accelerated data pre-processing pipelines implemented in DALI's python API.

nikhil-sk/djl

An Engine-Agnostic Deep Learning Framework in Java

nikhil-sk/djl-demo

Demo applications showcasing DJL

nikhil-sk/djl-serving

A universal scalable machine learning model deployment solution

nikhil-sk/fastertransformer_backend

nikhil-sk/fil_backend

FIL backend for the Triton Inference Server

nikhil-sk/identity_backend

Example Triton backend that demonstrates most of the Triton Backend API.

nikhil-sk/onnxruntime_backend

The Triton backend for the ONNX Runtime.

nikhil-sk/python_backend

Triton backend that enables pre-process, post-processing and other logic to be implemented in Python.

nikhil-sk/pytorch_backend

The Triton backend for the PyTorch TorchScript models.

nikhil-sk/repeat_backend

An example Triton backend that demonstrates sending zero, one, or multiple responses for each request.

nikhil-sk/sagemaker-huggingface-inference-toolkit

nikhil-sk/sagemaker-inference-toolkit

Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

nikhil-sk/sagemaker-mxnet-inference-toolkit

Toolkit for allowing inference and serving with MXNet in SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers.

nikhil-sk/sagemaker-python-sdk

A library for training and deploying machine learning models on Amazon SageMaker

nikhil-sk/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.

nikhil-sk/serve

Model Serving on PyTorch

nikhil-sk/server

The Triton Inference Server provides an optimized cloud and edge inferencing solution.

nikhil-sk/square_backend

Simple Triton backend used for testing.

nikhil-sk/tensorflow_backend

The Triton backend for TensorFlow 1 and TensorFlow 2.

nikhil-sk/TensorRT-LLM

TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.

nikhil-sk/tensorrt_backend

The Triton backend for TensorRT.

nikhil-sk/tensorrtllm_backend

The Triton TensorRT-LLM Backend

nikhil-sk/third_party

Third-party source packages that are modified for use in Triton.