Showing 3 open source projects for "qiper.ru/disk-cleaner"

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  • AI-generated apps that pass security review Icon
    AI-generated apps that pass security review

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  • 1
    GLM-4.7

    GLM-4.7

    Advanced language and coding AI model

    ...The model introduces stronger “thinking before acting” behavior, improving stability and accuracy in complex agent frameworks like Claude Code, Cline, and Roo Code. GLM-4.7 also advances “vibe coding,” producing cleaner, more modern UIs, better-structured webpages, and visually improved slide layouts. Its tool-use capabilities are substantially enhanced, with notable improvements in browsing, search, and tool-integrated reasoning tasks. Overall, GLM-4.7 shows broad performance upgrades across coding, reasoning, chat, creative writing, and role-play scenarios.
    Downloads: 332 This Week
    Last Update:
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  • 2
    StudioOllamaUI

    StudioOllamaUI

    StudioOllamaUI is a local, portable interface for Ollama

    ...No Python, no libraries, no drama. 100% Portable: Just like a portable browser. Unzip, run, and that's it. It doesn't clutter your registry or leave traces on your disk. AI for Everyone: No expensive GPU? No problem. Optimized to run smoothly on your CPU and RAM. Total Privacy: Everything stays on your machine. No data leaves for the cloud, and no hidden files are left on your system.
    Downloads: 23 This Week
    Last Update:
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  • 3
    DiT (Diffusion Transformers)

    DiT (Diffusion Transformers)

    Official PyTorch Implementation of "Scalable Diffusion Models"

    ...Unlike CNN-based diffusion models, DiT represents the diffusion process in the latent space and processes image tokens through transformer blocks with learned positional encodings, offering scalability and superior sample quality. The model architecture parallels large language models but for image tokens—each block refines noisy latent representations toward cleaner outputs through iterative denoising steps. DiT achieves strong results on benchmarks like ImageNet and LSUN while being architecturally simple and highly modular. It supports variable resolution, conditioning on class or text embeddings, and integration with latent autoencoders (like those used in Stable Diffusion).
    Downloads: 0 This Week
    Last Update:
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