4 projects for "assembly source code" with 2 filters applied:

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  • 1
    nlp-tutorial

    nlp-tutorial

    Natural Language Processing Tutorial for Deep Learning Researchers

    nlp-tutorial is an educational repository that implements influential natural language processing models in concise PyTorch examples. Most implementations use fewer than 100 lines of executable code, making the architectures easier to inspect and modify. The curriculum begins with neural language models, Word2Vec, and FastText. It then covers TextCNN, recurrent networks, LSTM, bidirectional LSTM, sequence-to-sequence learning, and attention. Later examples implement the Transformer and BERT...
    Downloads: 3 This Week
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  • 2
    XLM (Cross-lingual Language Model)

    XLM (Cross-lingual Language Model)

    PyTorch original implementation of Cross-lingual Language Model

    XLM (Cross-lingual Language Model) is a family of multilingual pretraining methods that align representations across languages to enable strong zero-shot transfer. It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence...
    Downloads: 0 This Week
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  • 3
    nlp-roadmap

    nlp-roadmap

    ROADMAP(Mind Map) and KEYWORD for students

    nlp-roadmap is a visual learning guide for students exploring natural language processing and related foundations. It organizes essential keywords into semantic mind maps rather than presenting a conventional textbook or code library. The material begins with probability and statistics, then progresses through machine learning and text mining. Its final section maps major concepts and methods within natural language processing. The diagrams are intended to suggest a study path, while...
    Downloads: 0 This Week
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  • 4

    TEES

    Turku Event Extraction System

    Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information.
    Downloads: 2 This Week
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