Showing 2 open source projects for "nvidia 3090"

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  • The Most Powerful Software Platform for EHSQ and ESG Management Icon
    The Most Powerful Software Platform for EHSQ and ESG Management

    Addresses the needs of small businesses and large global organizations with thousands of users in multiple locations.

    Choose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
  • Safety Management Platform | SafetyIQ Icon
    Safety Management Platform | SafetyIQ

    Keep your workers safe, no matter where they are

    SafetyIQ is revolutionizing the way businesses approach safety. As a leading provider of comprehensive workplace safety software, we cater to four key areas: Mobile Worker Safety, EHS (Environment, Health, and Safety), Fatigue Management, and Training. Our platform is designed to safeguard your workers, no matter their location or task, ensuring all-around safety compliance. Unlike most safety software providers that only react to incidents or implement proactive measures, SafetyIQ introduces a third pillar to safety management - predictive analytics. We transform the untapped wealth of safety data within your organization into actionable insights to inform safety strategies, mitigating risks even before they aris
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    FastChat

    FastChat

    Open platform for training, serving, and evaluating language models

    FastChat is an open platform for training, serving, and evaluating large language model-based chatbots. If you do not have enough memory, you can enable 8-bit compression by adding --load-8bit to the commands above. This can reduce memory usage by around half with slightly degraded model quality. It is compatible with the CPU, GPU, and Metal backend. Vicuna-13B with 8-bit compression can run on a single NVIDIA 3090/4080/T4/V100(16GB) GPU. In addition to that, you can add --cpu-offloading...
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  • 2
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    ... memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
    Downloads: 0 This Week
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