Showing 4 open source projects for "hardware"

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    FastSD CPU

    FastSD CPU

    Fast stable diffusion on CPU and AI PC

    ...With support for performance-oriented libraries such as OpenVINO and hardware acceleration on platforms like Intel AI PCs, FastSD CPU aims to shrink generation times dramatically compared with naive CPU implementations.
    Downloads: 32 This Week
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  • 2
    FLUX.1

    FLUX.1

    Official inference repo for FLUX.1 models

    FLUX.1 repository contains inference code and tooling for the FLUX.1 text-to-image diffusion models, enabling developers and researchers to generate and edit images from natural-language prompts using open-weight versions of the model on their own hardware or within custom applications. The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic fidelity. This repo focuses on running the open-source model variants efficiently, providing scripts, model loading logic, and examples for local installations, and supports integration with Python toolchains like PyTorch and popular generative pipelines. ...
    Downloads: 94 This Week
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  • 3
    Diffusion Bee

    Diffusion Bee

    Diffusion Bee is the easiest way to run Stable Diffusion locally

    ...Users can generate images from text prompts, perform image-to-image transformations, and apply additional features like inpainting, outpainting, and model-based upscaling directly within a clean graphical interface. It’s optimized for Apple hardware performance and can automatically manage features like ControlNet, LoRA models, and advanced prompt options without exposing complexity to the user.
    Downloads: 11 This Week
    Last Update:
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  • 4
    Z-Image

    Z-Image

    Image generation model with single-stream diffusion transformer

    Z-Image is an efficient, open-source image generation foundation model built to make high-quality image synthesis more accessible. With just 6 billion parameters — far fewer than many large-scale models — it uses a novel “single-stream diffusion Transformer” architecture to deliver photorealistic image generation, demonstrating that excellence does not always require extremely large model sizes. The project includes several variants: Z-Image-Turbo, a distilled version optimized for speed and...
    Downloads: 22 This Week
    Last Update:
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