Showing 5 open source projects for "web mapping framework"

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    ralph-loop-agent

    ralph-loop-agent

    Continuous Autonomy for the AI SDK

    ralph-loop-agent is an experimental autonomous agent framework from Vercel Labs that brings continuous autonomy to the AI SDK, enabling AI solutions to perform long-running, iterative tasks without manual stop/start intervention. Rather than simply answering a single request and stopping, Ralph Loop implements a loop control architecture that allows an agent to repeatedly evaluate its progress, adjust its approach, and continue working toward a defined completion criteria until tasks are fully resolved. ...
    Downloads: 0 This Week
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  • 2
    CogVideo

    CogVideo

    Text and image to video generation: CogVideoX and CogVideo

    CogVideo is an open-source family of advanced video generation models that can create videos from text, images, or existing video inputs. Built on large-scale Transformer and diffusion architectures, it enables multimodal generation across text-to-video, image-to-video, and video continuation tasks. The latest CogVideoX models offer higher resolution outputs, longer video durations, and improved controllability through prompt engineering. The project includes tools for inference,...
    Downloads: 13 This Week
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  • 3
    HunyuanWorld 1.0

    HunyuanWorld 1.0

    Generating Immersive, Explorable, and Interactive 3D Worlds

    HunyuanWorld-1.0 is an open-source, simulation-capable 3D world generation model developed by Tencent Hunyuan that creates immersive, explorable, and interactive 3D environments from text or image inputs. It combines the strengths of video-based diversity and 3D-based geometric consistency through a novel framework using panoramic world proxies and semantically layered 3D mesh representations. This approach enables 360° immersive experiences, seamless mesh export for graphics pipelines, and...
    Downloads: 2 This Week
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  • 4
    MUSE

    MUSE

    A library for Multilingual Unsupervised or Supervised word Embeddings

    MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement.
    Downloads: 0 This Week
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  • 5
    CLIP-ViT-bigG-14-laion2B-39B-b160k

    CLIP-ViT-bigG-14-laion2B-39B-b160k

    CLIP ViT-bigG/14: Zero-shot image-text model trained on LAION-2B

    ...It achieves an impressive 80.1% top-1 accuracy on ImageNet-1k without any fine-tuning, showcasing its robustness in open-domain settings. Its training dataset is uncurated and web-sourced, meaning it reflects the biases and risks of large-scale internet data. The model is intended for research use and is not recommended for real-world deployment without domain-specific testing and safety evaluations.
    Downloads: 0 This Week
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