Showing 4 open source projects for "stanford"

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  • 1
    Stanza

    Stanza

    Stanford NLP Python library for many human languages

    Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of...
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  • 2

    SPL Compiler

    Student Programming Language (SPL) a subset of PL/I

    Student Programming Language (SPL) compiles and executes programs written in a subset of PL/I. SPL was created by David B. Wortman in 1969 at Stanford University as a teaching tool for beginning programmers. In 1970 the compiler was modified by Robin A. Vowels at Royal Melbourne Institute of Technology to be more compatible with the PL/I language. The compiler is written in XPL using an MSP parser. XPL is described in the book "A Compiler Generator" by McKeeman, Horning and Wortman.
    Downloads: 1 This Week
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  • 3
    PyTorch Natural Language Processing

    PyTorch Natural Language Processing

    Basic Utilities for PyTorch Natural Language Processing (NLP)

    ... this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings.
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  • 4
    sjcl

    sjcl

    Stanford Javascript Crypto Library

    The Stanford Javascript Crypto Library is a project by the Stanford Computer Security Lab to build a secure, powerful, fast, small, easy-to-use, cross-browser library for cryptography in Javascript. SJCL is small but powerful. The minified version of the library is under 6.4KB compressed, and yet it posts impressive speed results. SJCL is secure. It uses the industry-standard AES algorithm at 128, 192 or 256 bits; the SHA256 hash function; the HMAC authentication code; the PBKDF2 password...
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