Showing 4 open source projects for "dictionary generation"

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  • 1
    makemore

    makemore

    An autoregressive character-level language model for making more

    makemore is a compact educational framework for training character-level language models on line-separated text datasets. Given examples such as personal names, company names, or dictionary words, it learns their statistical structure and generates new examples with similar patterns. The project intentionally keeps most functionality in one hackable Python file and requires only PyTorch. It includes implementations ranging from simple bigram models to MLPs, recurrent networks, LSTMs, GRUs,...
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  • 2
    Tensorflow Transformers

    Tensorflow Transformers

    State of the art faster Transformer with Tensorflow 2.0

    Imagine auto-regressive generation to be 90x faster. tf-transformers (Tensorflow Transformers) is designed to harness the full power of Tensorflow 2, designed specifically for Transformer based architecture. These models can be applied on text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages.
    Downloads: 0 This Week
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  • 3
    Tofu

    Tofu

    Tofu is a Python tool for generating synthetic UK Biobank data

    Tofu is a Python library for generating synthetic UK Biobank data. The UK Biobank is a large open-access prospective research cohort study of 500,000 middle-aged participants recruited in England, Scotland and Wales. The study has collected and continues to collect extensive phenotypic and genotypic detail about its participants, including data from questionnaires, physical measures, sample assays, accelerometry, multimodal imaging, genome-wide genotyping and longitudinal follow-up for a...
    Downloads: 0 This Week
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  • 4
    FavFreak

    FavFreak

    Favicon hash–based reconnaissance tool for security research

    FavFreak is an open source reconnaissance tool designed to assist security researchers, bug bounty hunters, and penetration testers in identifying web technologies using favicon hashes. It works by taking one or more URLs as input and automatically retrieving the favicon.ico file associated with each target website. After fetching the favicon, it calculates a hash value and organizes the scanned domains, subdomains, or IP addresses according to these hashes. FavFreak then compares the...
    Downloads: 0 This Week
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