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  • SearchSearch thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
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  • Displaying 14 results
    meta-llama-2-70b-chat
    NVIDIA
    NVIDIA NIM for GPU accelerated Llama 2 70B inference through OpenAI compatible APIs
    Container
    Isaac Sim
    NVIDIA
    NVIDIA Isaac Sim™ is a robotics and AI simulation application framework built on NVIDIA Omniverse™. Isaac Sim has essential features for building virtual robotic worlds and experiments.
    Container
    PyG
    NVIDIA
    PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
    Container
    AlphaFold2-Multimer
    Google
    A widely used model for predicting the 3D structures of proteins from their amino acid sequences. This version of the container supports multimers, i.e. proteins made up of 2 or more polypeptide chains.
    Container
    MAISI NIM
    NVIDIA
    MAISI NIM generated high-quality synthetic CT images with or without anatomical annotations.
    Container
    Foundational Flywheel Server
    NVIDIA
    Turn workload evaluation and optimization requests into a fully automated, end-to-end workflow across many specialized micro-services with the Flywheel orchestrator control-plane service.
    Container
    NVIDIA Data Flywheel Blueprint
    NVIDIA
    Deploy the NVIDIA Data Flywheel Foundational Blueprint on Kubernetes using Helm charts for scalable, production-ready environments.
    Helm Chart
    Nemotron-4-340B-Base
    NVIDIA
    Nemotron-4-340B-Base
    Model
    NeMo Data Designer Docker Compose
    NVIDIA
    A docker-compose file to simplify quickstart deployments of NeMo Data Designer.
    Resource
    TAO with Synthetic Data
    Rendedred.ai
    Jupyter Notebook for training FasterRCNN with Rendered.ai user generated datasets.
    Resource
    TTS En FastPitch SpectrogramEnhancer For-ASR-Finetuning
    NVIDIA
    This collection contains FastPitch and Spectrogram Enhancer models. Main use case is English ASR domain fine-tuning. Direct TTS use is not advised.
    Model
    Consistency Distilled Synthetic Protein Database
    NVIDIA
    This resource consists of the Consistency Distilled Dataset used for Proteina-Atomistica model training.
    Resource
    Cosmos World Foundation Models
    NVIDIA
    Cosmos World Foundation Models: A family of highly performant pre-trained world foundation models purpose-built for generating physics-aware videos and world states for physical AI development.
    Collection
    Proteina-Atomistica
    —
    This collections consists of the training data for the Proteina-Atomistica all-atom protein structure generative model.
    Collection

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