Pinned Repositories
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
amazon-sagemaker-examples-community
aresdb
A GPU-powered real-time analytics storage and query engine.
benchmark
benchmark-locust
Benchmark suite for LLMs from Fireworks.ai
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.
djl-serving
A universal scalable machine learning model deployment solution
folly
An open-source C++ library developed and used at Facebook.
torchserve_perf
lxning's Repositories
lxning/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
lxning/benchmark
lxning/benchmark-locust
Benchmark suite for LLMs from Fireworks.ai
lxning/torchserve_perf
lxning/amazon-sagemaker-examples-community
lxning/aresdb
A GPU-powered real-time analytics storage and query engine.
lxning/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.
lxning/djl-serving
A universal scalable machine learning model deployment solution
lxning/folly
An open-source C++ library developed and used at Facebook.
lxning/lm-evaluation-harness
A framework for few-shot evaluation of language models.
lxning/multi-model-server
Multi Model Server is a tool for serving neural net models for inference
lxning/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
lxning/sagemaker-pytorch-training-toolkit
Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
lxning/serve
Model Serving on PyTorch
lxning/server
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
lxning/zap
Blazing fast, structured, leveled logging in Go.