Showing 3 open source projects for "yolov4.weights"

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    Code World Model (CWM)

    Code World Model (CWM)

    Research code artifacts for Code World Model (CWM)

    CWM (Code World Model) is a 32-billion-parameter open-weights language model. It is developed by Meta for enhancing code generation and reasoning about programs. It is explicitly trained on execution traces, action-observation trajectories, and agentic interactions in controlled environments. It has been developed to better capture how code, actions, and state interact over time. The repository provides inference code, reproducibility scripts, prompt guides, and more.
    Downloads: 0 This Week
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  • 2
    MiniMax-M2.1

    MiniMax-M2.1

    MiniMax M2.1, a SOTA model for real-world dev & agents.

    MiniMax-M2.1 is an open-source, state-of-the-art agentic language model released to democratize high-performance AI capabilities. It goes beyond a simple parameter upgrade, delivering major gains in coding, tool use, instruction following, and long-horizon planning. The model is designed to be transparent, controllable, and accessible, enabling developers to build autonomous systems without relying on closed platforms. MiniMax-M2.1 excels in real-world software engineering tasks, including...
    Downloads: 6 This Week
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  • 3
    mac code

    mac code

    Claude Code, but it runs on your Mac for free

    mac code is a local AI coding agent designed to run large language models directly on Apple Silicon machines without relying on cloud services, effectively transforming a Mac into a self-contained AI development environment. The project focuses on enabling models that traditionally exceed available RAM to run efficiently by streaming model weights from SSD storage, thereby overcoming hardware limitations through innovative memory management techniques. It operates as a CLI-based assistant that routes user prompts into different execution paths such as chat, shell commands, or web search, functioning as a multi-purpose development agent. The system integrates with inference engines like llama.cpp and Apple’s MLX framework, allowing users to run models up to 35B parameters locally with varying performance trade-offs.
    Downloads: 0 This Week
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