NVIDIA Corporation
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- Model-Optimizer Public
A unified library of SOTA model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
NVIDIA/Model-Optimizer’s past year of commit activity - cuda-quantum Public
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
NVIDIA/cuda-quantum’s past year of commit activity - NeMo-Retriever Public
NeMo Retriever Library is a scalable, performance-oriented document content and metadata extraction microservice. NeMo Retriever extraction uses specialized NVIDIA NIM microservices to find, contextualize, and extract text, tables, charts and images that you can use in downstream generative applications.
NVIDIA/NeMo-Retriever’s past year of commit activity - NeMo-Agent-Toolkit Public
The NVIDIA NeMo Agent toolkit is an open-source library for efficiently connecting and optimizing teams of AI agents.
NVIDIA/NeMo-Agent-Toolkit’s past year of commit activity - TensorRT-LLM Public
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
NVIDIA/TensorRT-LLM’s past year of commit activity
