Showing 4 open source projects for "language programming for android"

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  • 1
    Open Interpreter

    Open Interpreter

    A natural language interface for computers

    Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. Runs locally or via configured remote LLM servers/inference backends, giving flexibility to use models you trust or have...
    Downloads: 7 This Week
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  • 2
    Milvus Bootcamp

    Milvus Bootcamp

    Dealing with all unstructured data, such as reverse image search

    Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications.
    Downloads: 0 This Week
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  • 3
    Automatic text summarizer

    Automatic text summarizer

    Module for automatic summarization of text documents and HTML pages

    Sumy is an automatic text summarization library that provides multiple algorithms for extracting key content from documents and articles. Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains a simple evaluation framework for text summaries. Implemented summarization methods are described in the documentation. I also maintain a list of alternative implementations of the summarizers in various programming languages.
    Downloads: 2 This Week
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  • 4
    GT NLP Class

    GT NLP Class

    Course materials for Georgia Tech CS 4650 and 7650

    This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). ...
    Downloads: 1 This Week
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