Showing 4 open source projects for "python framework"

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  • 1
    BitNet

    BitNet

    Inference framework for 1-bit LLMs

    BitNet (bitnet.cpp) is a high-performance inference framework designed to optimize the execution of 1-bit large language models, making them more efficient for edge devices and local deployment. The framework offers significant speedups and energy reductions, achieving up to 6.17x faster performance on x86 CPUs and 70% energy savings, allowing the running of models such as the BitNet b1.58 100B with impressive efficiency. With support for lossless inference and enhanced processing power,...
    Downloads: 3 This Week
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  • 2
    MuJoCo MPC

    MuJoCo MPC

    Real-time behaviour synthesis with MuJoCo, using Predictive Control

    ...The system supports multi-shooting optimization, enabling precise motion planning across diverse domains like quadruped locomotion, humanoid tracking, and dexterous manipulation. In addition to its C++ core, MJPC includes an experimental Python API, enabling integration with custom models and MuJoCo tasks for flexible scripting and experimentation.
    Downloads: 0 This Week
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  • 3
    fairseq2

    fairseq2

    FAIR Sequence Modeling Toolkit 2

    fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a...
    Downloads: 1 This Week
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  • 4
    DeepSDF

    DeepSDF

    Learning Continuous Signed Distance Functions for Shape Representation

    DeepSDF is a deep learning framework for continuous 3D shape representation using Signed Distance Functions (SDFs), as presented in the CVPR 2019 paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation by Park et al. The framework learns a continuous implicit function that maps 3D coordinates to their corresponding signed distances from object surfaces, allowing compact, high-fidelity shape modeling. Unlike traditional discrete voxel grids or meshes, DeepSDF...
    Downloads: 0 This Week
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