Showing 4 open source projects for "character"

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    Train ML Models With SQL You Already Know

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  • 1
    FLUX.2

    FLUX.2

    Official inference repo for FLUX.2 models

    ...FLUX.2 is built with a modern architecture (a flow-matching transformer + a revamped VAE + a strong vision-language encoder), enabling strong prompt adherence, correct rendering of text/typography in images, reliable lighting, layout, and physical realism, and consistent style/character/product identity across multiple generations or edits.
    Downloads: 30 This Week
    Last Update:
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  • 2
    HunyuanImage-3.0

    HunyuanImage-3.0

    A Powerful Native Multimodal Model for Image Generation

    HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter...
    Downloads: 6 This Week
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  • 3
    KoboldCpp

    KoboldCpp

    Run GGUF models easily with a UI or API. One File. Zero Install.

    KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. It's a single self-contained distributable that builds off llama.cpp and adds many additional powerful features.
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    Downloads: 305 This Week
    Last Update:
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  • 4
    CLIP Guided Diffusion

    CLIP Guided Diffusion

    A CLI tool/python module for generating images from text

    ...Sacrifices accuracy/alignment for quicker runtime. options: - 25, 50, 150, 250, 500, 1000, ddim25,ddim50,ddim150, ddim250,ddim500,ddim1000 (default: 1000) Prepending a number with ddim will use the ddim scheduler. e.g. ddim25 will use the 25 timstep ddim scheduler. This method may be better at shorter timestep_respacing values. Multiple prompts can be specified with the | character. You may optionally specify a weight for each prompt.
    Downloads: 0 This Week
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