Showing 4 open source projects for "linux desktop"

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    FastSD CPU

    FastSD CPU

    Fast stable diffusion on CPU and AI PC

    FastSD CPU is an optimized fork of Stable Diffusion designed to run efficiently on CPUs and devices without dedicated GPUs by leveraging Latent Consistency Models and Adversarial Diffusion Distillation techniques that accelerate inference. It focuses on bringing fast text-to-image generation to mainstream hardware like desktop CPUs, lower-end laptops, or edge devices without requiring high-end graphics processors. The repository contains multiple interfaces including a desktop GUI for simple...
    Downloads: 12 This Week
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  • 2
    LTX-2

    LTX-2

    Python inference and LoRA trainer package for the LTX-2 audio–video

    LTX-2 is a powerful, open-source toolkit developed by Lightricks that provides a modular, high-performance base for building real-time graphics and visual effects applications. It is architected to give developers low-level control over rendering pipelines, GPU resource management, shader orchestration, and cross-platform abstractions so they can craft visually compelling experiences without starting from scratch. Beyond basic rendering scaffolding, LTX-2 includes optimized math libraries,...
    Downloads: 16 This Week
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  • 3
    LeWorldModel

    LeWorldModel

    Official code base for LeWorldModel: Stable End-to-End Joint-Embedding

    LeWorldModel is a minimalist tiling window manager designed for the X11 windowing system, focusing on simplicity, performance, and efficient use of screen space. It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration...
    Downloads: 2 This Week
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  • 4
    MiniMax-M2.5

    MiniMax-M2.5

    State of the art LLM and coding model

    MiniMax-M2.5 is a state-of-the-art foundation model extensively trained with reinforcement learning across hundreds of thousands of real-world environments. It delivers leading performance in coding, agentic tool use, search, and complex office workflows, achieving top benchmark scores such as 80.2% on SWE-Bench Verified and 76.3% on BrowseComp. Designed to reason efficiently and decompose tasks like an experienced architect, M2.5 plans features, structure, and system design before...
    Downloads: 2 This Week
    Last Update:
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