Showing 4 open source projects for "nvidia"

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    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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    Zendesk: The Complete Customer Service Solution

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  • 1
    Thrust

    Thrust

    The C++ parallel algorithms library

    ...It builds on top of established parallel programming frameworks (such as CUDA, TBB, and OpenMP). It also provides a number of general-purpose facilities similar to those found in the C++ Standard Library. The NVIDIA C++ Standard Library is an open-source project; it is available on GitHub and included in the NVIDIA HPC SDK and CUDA Toolkit. If you have one of those SDKs installed, no additional installation or compiler flags are needed to use libcu++. Thrust is a header-only library; there is no need to build or install the project unless you want to run the Thrust unit tests.
    Downloads: 1 This Week
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  • 2
    GFPGAN

    GFPGAN

    GFPGAN aims at developing Practical Algorithms

    GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing...
    Downloads: 103 This Week
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  • 3
    Real-ESRGAN ncnn Vulkan

    Real-ESRGAN ncnn Vulkan

    NCNN implementation of Real-ESRGAN

    ...It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. The Vulkan backend enables fast execution on GPUs from different vendors (Intel/AMD/Nvidia) with broad support, making it suitable for non-Python environments, production systems, or performance-constrained setups.
    Downloads: 53 This Week
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  • 4
    MXLib is a C++ wrapper around the Intel® Integrated Performance Primitives (IPP) library and NVidia NPP CUDA library. You can use either IPP code (or a subset of functions that do not require IPP) on the CPU side, or use NPP/CUDA on the GPU side, or use both together. The function syntax is similar to that found in MatLab and the library is designed to make it easy to port your code from MatLab to C++. The idea is to provide Scientists, Engineers, Researchers and other non full-time programmers an easy to use, high performance library of functions.
    Downloads: 0 This Week
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    Create and run cloud-based virtual machines.

    Secure and customizable compute service that lets you create and run virtual machines.

    Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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