Showing 7 open source projects for "computer system optimization"

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  • 1
    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: 7 This Week
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  • 2
    CogView4

    CogView4

    CogView4, CogView3-Plus and CogView3(ECCV 2024)

    ...It emphasizes bilingual usability, making it well-suited for cross-lingual multimodal applications. The model also supports fine-tuning and downstream customization, extending its applicability to creative content generation, human–computer interaction, and research on vision-language alignment.
    Downloads: 2 This Week
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  • 3
    Lyra 2

    Lyra 2

    Project Lyra: Open Generative 3D World Models

    ...It enables the creation of fully explorable 3D environments from minimal inputs such as a single image or video, leveraging self-distillation methods to generate consistent spatial representations. The system evolves across versions, with newer iterations introducing long-horizon generation and improved 3D consistency across frames. It combines elements of computer vision, generative modeling, and spatial intelligence to produce dynamic and navigable virtual worlds. The architecture is designed to handle both 3D and 4D scene generation, making it suitable for applications such as simulation, gaming, and virtual environments. ...
    Downloads: 0 This Week
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  • 4
    DeepSeek Math

    DeepSeek Math

    Pushing the Limits of Mathematical Reasoning in Open Language Models

    ...The goal is to push DeepSeek’s performance in domains that require rigorous symbolic steps, calculus, linear algebra, number theory, or multi-step derivations. The repo may also include modules that integrate external computational tools (e.g. a CAS / computer algebra system) or calculator assistance backends to enhance correctness. Because math reasoning is a high bar for LLMs, DeepSeek-Math aims to showcase their model’s ability not just in natural text but in precise formal reasoning.
    Downloads: 2 This Week
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  • 5
    MuJoCo MPC

    MuJoCo MPC

    Real-time behaviour synthesis with MuJoCo, using Predictive Control

    ...MJPC integrates a high-performance GUI and multiple predictive control algorithms, including iLQG, gradient descent, and Predictive Sampling — a competitive, derivative-free method that achieves robust real-time 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: 1 This Week
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  • 6
    MiniMax-M2.7

    MiniMax-M2.7

    Self-evolving AI model for agents, coding, and complex workflows

    MiniMax-M2.7 is a large-scale open-weight language model designed for advanced agent-based workflows, professional software engineering, and complex productivity tasks. With 229B parameters, it introduces a self-evolution framework in which the model actively improves its own capabilities by updating memory, generating skills, and iterating through reinforcement learning experiments. This process enables it to autonomously refine systems, achieving measurable performance gains such as a 30%...
    Downloads: 0 This Week
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  • 7
    Llama-3.2-1B

    Llama-3.2-1B

    Llama 3.2–1B: Multilingual, instruction-tuned model for mobile AI

    meta-llama/Llama-3.2-1B is a lightweight, instruction-tuned generative language model developed by Meta, optimized for multilingual dialogue, summarization, and retrieval tasks. With 1.23 billion parameters, it offers strong performance in constrained environments like mobile devices, without sacrificing versatility or multilingual support. It is part of the Llama 3.2 family, trained on up to 9 trillion tokens and aligned using supervised fine-tuning, preference optimization, and safety...
    Downloads: 0 This Week
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