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- C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
- 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.
- BioNeMo Framework: For building and adapting AI models in drug discovery at scale
- CUDA Core Compute Libraries
Megatron-LM
PublicOngoing research training transformer models at scaleskyhook
PublicNVFlare
PublicNVIDIA Federated Learning Application Runtime EnvironmentNVSentinel
PublicTensorRT-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.warp
PublicA Python framework for accelerated simulation, data generation and spatial computing.gpu-operator
Publicnumba-cuda
Publicspark-rapids-jni
Publicnv-ingest
PublicNeMo 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-resiliency-ext
Publiccuda-python
Publicgpu-driver-container
Publiccuda-q-academic
PublicTileGym
Publicearth2studio
PublicOpen-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.hpc-container-maker
PublicHPC Container Makeraistore
PublicAIStore: scalable storage for AI applications