Showing 4 open source projects for "third party"

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  • 1
    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
    Last Update:
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  • 2
    DeepSeek-OCR

    DeepSeek-OCR

    Contexts Optical Compression

    ...The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body text, interpreting tables, or recognizing handwritten versus printed words. It supports local deployment, enabling organizations concerned about privacy or latency to run the pipeline on-premises rather than send sensitive documents to third-party cloud services. The codebase is written in Python with a focus on modularity: you can swap preprocessing, recognition, and post-processing components as needed for custom workflows.
    Downloads: 9 This Week
    Last Update:
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  • 3
    MiniMind-O

    MiniMind-O

    A 0.1B Omni model trained from scratch

    ...It includes both mini and full training data paths, allowing learners to run a complete workflow quickly or reproduce the released model setup more closely. The implementation emphasizes native PyTorch code instead of relying on high-level third-party abstractions. minimind-o is most useful for developers and researchers who want to understand how multimodal and speech-capable AI systems are built from the ground up.
    Downloads: 0 This Week
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  • 4
    OpenAI Harmony

    OpenAI Harmony

    Renderer for the harmony response format to be used with gpt-oss

    ...The format is essential for ensuring gpt-oss models operate correctly, as they are trained to rely on this structure for generating and organizing their responses. For users accessing gpt-oss through third-party providers like HuggingFace, Ollama, or vLLM, Harmony formatting is handled automatically, but developers building custom inference setups must implement it directly. With its flexible design, Harmony serves as the foundation for creating more interpretable, controlled, and extensible interactions with open-weight language models.
    Downloads: 1 This Week
    Last Update:
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