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    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

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    LLaMA 3

    LLaMA 3

    The official Meta Llama 3 GitHub site

    This repository is the former home for Llama 3 model artifacts and getting-started code, covering pre-trained and instruction-tuned variants across multiple parameter sizes. It introduced the public packaging of weights, licenses, and quickstart examples that helped developers fine-tune or run the models locally and on common serving stacks. As the Llama stack evolved, Meta consolidated repositories and marked this one deprecated, pointing users to newer, centralized hubs for models,...
    Downloads: 32 This Week
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  • 2
    GLM-V

    GLM-V

    GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning

    ...GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image, video, document, GUI, and grounding tasks. It introduces hybrid training for broad-spectrum reasoning and a Thinking Mode switch to balance speed and depth of reasoning. GLM-4.1V-9B-Thinking incorporates reinforcement learning with curriculum sampling (RLCS) and Chain-of-Thought reasoning, outperforming models much larger in scale (e.g., Qwen-2.5-VL-72B) across many benchmarks.
    Downloads: 0 This Week
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    ChatGLM-6B

    ChatGLM-6B

    ChatGLM-6B: An Open Bilingual Dialogue Language Model

    ...The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference (INT4, INT8) to reduce GPU memory requirements. Automatic mode switching between precision/memory tradeoffs (full/quantized).
    Downloads: 0 This Week
    Last Update:
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  • 4
    PKU Beaver

    PKU Beaver

    Constrained Value Alignment via Safe Reinforcement Learning

    ...These annotations include categories such as harmful language, unethical behavior, privacy violations, and other sensitive topics. By incorporating constraint-based optimization methods, Safe-RLHF trains models that balance reward objectives with safety requirements, ensuring that harmful outputs are penalized during training.
    Downloads: 0 This Week
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