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- NeMo Retriever extraction 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 device plugin for Kubernetes
- GPU accelerated decision optimization
numba-cuda
Public- Ongoing research training transformer models at scale
- A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM or TensorRT to optimize inference speed.
TensorRT-LLM
PublicTensorRT 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.- BioNeMo Framework: For building and adapting AI models in drug discovery at scale
- Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
edk2-edkrepo-manifest
Public- Documentation repository for NVIDIA Cloud Native Technologies
edk2-infineon
Publicedk2-platforms
Public