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  • 1
    R-KV

    R-KV

    Redundancy-aware KV Cache Compression for Reasoning Models

    R-KV introduces a method for compressing the KV cache during decoding, allowing models to maintain reasoning performance while reducing memory consumption and computational overhead. The approach focuses on identifying which attention heads and cache components are most important for maintaining reasoning quality, allowing less critical information to be compressed or discarded.
    Downloads: 0 This Week
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    H2O LLM Studio

    H2O LLM Studio

    Framework and no-code GUI for fine-tuning LLMs

    Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell.
    Downloads: 3 This Week
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  • 3
    Anomaly Detection Learning Resources

    Anomaly Detection Learning Resources

    Anomaly detection related books, papers, videos, and toolboxes

    ...It includes materials covering a wide range of anomaly detection domains, including time series data, graph data, tabular datasets, and real-time monitoring systems. By compiling resources from multiple programming ecosystems such as Python, R, and other machine learning platforms, the repository allows users to discover both research papers and practical implementations.
    Downloads: 0 This Week
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  • 4
    unit-minions

    unit-minions

    AI R&D Efficiency Improvement Research: Do-It-Yourself Training LoRA

    "AI R&D Efficiency Improvement Research: Do-It-Yourself Training LoRA", including Llama (Alpaca LoRA) model, ChatGLM (ChatGLM Tuning) related Lora training. Training content: user story generation, test code generation, code-assisted generation, text to SQL, text generation code.
    Downloads: 0 This Week
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