Showing 5 open source projects for "active"

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  • 1
    FlashInfer

    FlashInfer

    FlashInfer: Kernel Library for LLM Serving

    FlashInfer is a kernel library designed to enhance the serving of Large Language Models (LLMs) by optimizing inference performance. It provides a high-performance framework that integrates seamlessly with existing systems, aiming to reduce latency and improve efficiency in LLM deployments. FlashInfer supports various hardware architectures and is built to scale with the demands of production environments.
    Downloads: 132 This Week
    Last Update:
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  • 2
    optillm

    optillm

    Optimizing inference proxy for LLMs

    OptiLLM is an optimizing inference proxy for Large Language Models (LLMs) that implements state-of-the-art techniques to enhance performance and efficiency. It serves as an OpenAI API-compatible proxy, allowing for seamless integration into existing workflows while optimizing inference processes. OptiLLM aims to reduce latency and resource consumption during LLM inference.
    Downloads: 1 This Week
    Last Update:
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  • 3
    LMDeploy

    LMDeploy

    LMDeploy is a toolkit for compressing, deploying, and serving LLMs

    LMDeploy is a toolkit designed for compressing, deploying, and serving large language models (LLMs). It offers tools and workflows to optimize LLMs for production environments, ensuring efficient performance and scalability. LMDeploy supports various model architectures and provides deployment solutions across different platforms.
    Downloads: 0 This Week
    Last Update:
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  • 4
    LitGPT

    LitGPT

    20+ high-performance LLMs with recipes to pretrain, finetune at scale

    LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments.
    Downloads: 0 This Week
    Last Update:
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  • 5
    Medusa

    Medusa

    Framework for Accelerating LLM Generation with Multiple Decoding Heads

    Medusa is a framework aimed at accelerating the generation capabilities of Large Language Models (LLMs) by employing multiple decoding heads. This approach allows for parallel processing during text generation, significantly enhancing throughput and reducing response times. Medusa is designed to be simple to implement and integrates with existing LLM infrastructures, making it a practical solution for scaling LLM applications.
    Downloads: 0 This Week
    Last Update:
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