SriKrishna Paparaju's repositories
accelerate
🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
DALI
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
dbrx
Code examples and resources for DBRX, a large language model developed by Databricks
dcgm-exporter
NVIDIA GPU metrics exporter for Prometheus leveraging DCGM
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
DeepSpeed-MII
MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
DeepSpeedExamples
Example models using DeepSpeed
diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
dspy
DSPy: The framework for programming—not prompting—foundation models
faiss
A library for efficient similarity search and clustering of dense vectors.
gpu-operator
NVIDIA GPU Operator creates/configures/manages GPUs atop Kubernetes
graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
jupyterlab-nvdashboard
A JupyterLab extension for displaying dashboards of GPU usage.
kuberay
A toolkit to run Ray applications on Kubernetes
Megatron-LM
Ongoing research training transformer models at scale
mlflow
Open source platform for the machine learning lifecycle
nim-anywhere
Accelerate your Gen AI with NVIDIA NIM and NVIDIA AI Workbench
nim-deploy
A collection of YAML files, Helm Charts, Operator code, and guides to act as an example reference implementation for NVIDIA NIM deployment.
optimum
🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools
ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
streaming
A Data Streaming Library for Efficient Neural Network Training
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.
TensorRT-Model-Optimizer
TensorRT Model Optimizer is a unified library of state-of-the-art model optimization techniques such as quantization and sparsity. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM or TensorRT to optimize inference speed on NVIDIA GPUs.
torchtune
A Native-PyTorch Library for LLM Fine-tuning
transformers
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
triton
Development repository for the Triton language and compiler
vllm
A high-throughput and memory-efficient inference and serving engine for LLMs