Showing 4 open source projects for "optimize"

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    Qwen Code

    Qwen Code

    Qwen Code is a coding agent that lives in the digital world

    ...Users configure Qwen Code by setting API keys and endpoints, supporting both mainland China and international access. With Qwen Code, developers can explore codebases, refactor and optimize code, generate documentation, and automate repetitive tasks directly from the terminal.
    Downloads: 27 This Week
    Last Update:
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  • 2
    Ornith-1.0

    Ornith-1.0

    Ornith-1.0 is a self-improving open-source models for agentic coding

    ...The project presents 9B dense, 31B dense, 35B mixture-of-experts, and 397B mixture-of-experts variants. These models are post-trained on top of Gemma 4 and Qwen 3.5 foundations. Its training approach uses reinforcement learning to optimize both the solution and the scaffold that guides the solution process. The repository emphasizes benchmark performance on Terminal-Bench, SWE-bench, NL2Repo, OpenClaw, and SWE Atlas while keeping the project MIT licensed and globally accessible.
    Downloads: 3 This Week
    Last Update:
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  • 3
    deepclaude

    deepclaude

    Use Claude Code's agent loop with DeepSeek V4 Pro, OpenRouter & more

    ...The platform supports seamless backend switching in real time, allowing users to choose between cost efficiency and higher reasoning power when needed. It also includes built-in cost tracking and benchmarking tools to help developers monitor usage and optimize performance. Designed for flexibility and efficiency, deepclaude is ideal for developers who want powerful AI coding agents without the premium price tag.
    Downloads: 2 This Week
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  • 4
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. ...
    Downloads: 0 This Week
    Last Update:
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    Veeam Data Platform v13.1

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