Showing 4 open source projects for "study ai"

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  • 1
    Moondream

    Moondream

    Tiny vision language model

    Moondream is a creative code project and visual experimentation repository that explores generative graphics, aesthetic patterns, and interactive art through code. The project typically showcases procedural visualizations, algorithmic designs, and artistic experiments that push the boundaries of what can be expressed with programming languages and rendering frameworks. While the exact nature can vary by commit or branch, Moondream’s work often blends geometry, color theory, and motion to...
    Downloads: 1 This Week
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  • 2
    GPT-2 Output Dataset

    GPT-2 Output Dataset

    Dataset of GPT-2 outputs for research in detection, biases, and more

    The GPT-2 Output Dataset is a large collection of model-generated text, released by OpenAI alongside the GPT-2 research paper to study the behaviors and limitations of large language models. It contains 250,000 samples of GPT-2 outputs, generated with different sampling strategies such as top-k truncation, to highlight the diversity and quality of model completions. The dataset also includes corresponding human-written text for comparison, enabling researchers to explore methods for...
    Downloads: 0 This Week
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  • 3
    PRM800K

    PRM800K

    800,000 step-level correctness labels on LLM solutions to MATH problem

    PRM800K is a process supervision dataset accompanying the paper Let’s Verify Step by Step, providing 800,000 step-level correctness labels on model-generated solutions to problems from the MATH dataset. The repository releases the raw labels and the labeler instructions used in two project phases, enabling researchers to study how human raters graded intermediate reasoning. Data are stored as newline-delimited JSONL files tracked with Git LFS, where each line is a full solution sample that...
    Downloads: 2 This Week
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  • 4
    Improved GAN

    Improved GAN

    Code for the paper "Improved Techniques for Training GANs"

    Improved-GAN is the official code release from OpenAI accompanying the research paper Improved Techniques for Training GANs. It provides implementations of experiments conducted on datasets such as MNIST, SVHN, CIFAR-10, and ImageNet. The project focuses on demonstrating enhanced training methods for Generative Adversarial Networks, addressing stability and performance issues that were common in earlier GAN models. The repository includes training scripts, evaluation methods, and pretrained...
    Downloads: 0 This Week
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