Showing 7 open source projects for "compression"

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  • 1
    DeepSpeed

    DeepSpeed

    Deep learning optimization library: makes distributed training easy

    ...Achieve excellent system throughput and efficiently scale to thousands of GPUs 3. Train/Inference on resource constrained GPU systems 4. Achieve unprecedented low latency and high throughput for inference 5. Achieve extreme compression for an unparalleled inference latency and model size reduction with low costs DeepSpeed offers a confluence of system innovations, that has made large scale DL training effective, and efficient, greatly improved ease of use, and redefined the DL training landscape in terms of scale that is possible. These innovations such as ZeRO, 3D-Parallelism, DeepSpeed-MoE, ZeRO-Infinity, etc. fall under the training pillar.
    Downloads: 3 This Week
    Last Update:
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  • 2
    NNCF

    NNCF

    Neural Network Compression Framework for enhanced OpenVINO

    NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency.
    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: 14 This Week
    Last Update:
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  • 4
    AIMET

    AIMET

    AIMET is a library that provides advanced quantization and compression

    ...QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware accelerators. Quantized inference is significantly faster than floating point inference. For example, models that we’ve run on the Qualcomm® Hexagon™ DSP rather than on the Qualcomm® Kryo™ CPU have resulted in a 5x to 15x speedup. ...
    Downloads: 5 This Week
    Last Update:
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  • 5
    SparseML

    SparseML

    Libraries for applying sparsification recipes to neural networks

    SparseML is an optimization toolkit for training and deploying deep learning models using sparsification techniques like pruning and quantization to improve efficiency.
    Downloads: 0 This Week
    Last Update:
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  • 6
    Intel Extension for Transformers

    Intel Extension for Transformers

    Build your chatbot within minutes on your favorite device

    Intel Extension for Transformers is an innovative toolkit designed to accelerate Transformer-based models on Intel platforms, including CPUs and GPUs. It offers state-of-the-art compression techniques for Large Language Models (LLMs) and provides tools to build chatbots within minutes on various devices. The extension aims to optimize the performance of Transformer-based models, making them more efficient and accessible.
    Downloads: 0 This Week
    Last Update:
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  • 7
    FastChat

    FastChat

    Open platform for training, serving, and evaluating language models

    ...This requires 8-bit compression to be enabled and the bitsandbytes package to be installed, which is only available on linux operating systems.
    Downloads: 0 This Week
    Last Update:
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