Showing 3 open source projects for "no knowledge"

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  • 1
    HunyuanImage-3.0

    HunyuanImage-3.0

    A Powerful Native Multimodal Model for Image Generation

    ...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 counts without linear inference cost explosion. The model is intended to be competitive with closed-source image generation systems, aiming for high fidelity, prompt adherence, fine detail, and even “world knowledge” reasoning (i.e. leveraging context, semantics, or common sense in generation). The GitHub repo includes code, scripts, model loading instructions, inference utilities, prompt handling, and integration with standard ML tooling (e.g. Hugging Face / Transformers).
    Downloads: 3 This Week
    Last Update:
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  • 2
    GLM-Image

    GLM-Image

    GLM-Image: Auto-regressive for Dense-knowledge and High-fidelity Image

    ...Because it blends linguistic reasoning with image synthesis, GLM-Image produces visual outputs where semantic relationships and textual accuracy are prioritized alongside artistic style and realism, and its model structure enables it to handle dense visual knowledge tasks that challenge many pure diffusion models. The model’s design and weights are available under an open-source license that encourages experimentation, integration, and deployment across a range of creative workflows.
    Downloads: 1 This Week
    Last Update:
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  • 3
    Ian Xiaohei Illustrations

    Ian Xiaohei Illustrations

    Chinese Little Black Weird Text Illustration Generation Skill

    ...Its default style uses a 16:9 white-background composition with rough hand-drawn lines and small red, orange, or blue annotation marks. It is especially useful for knowledge creators who want recognizable article visuals without designing from scratch. The project works as a reusable creative instruction layer for AI-assisted content production.
    Downloads: 10 This Week
    Last Update:
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