Showing 4 open source projects for "summarization"

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  • 1
    txtai

    txtai

    Build AI-powered semantic search applications

    ..., models can understand concepts in documents, audio, images and more. Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. The following applications are powered by txtai.
    Downloads: 0 This Week
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  • 2
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated...
    Downloads: 0 This Week
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  • 3
    Reminiscence

    Reminiscence

    Self-Hosted Bookmark And Archive Manager

    .... Automatic summarization of HTML content. Special readability mode. Search bookmarks according to url, title, tags or summary. Supports multiple user accounts. Supports public and group directories for every user. Upload any file from web interface for archiving. Easy to use admin interface for managing multiple users. Import bookmarks from Netscape Bookmark HTML file format. Supports streaming of archived media elements.
    Downloads: 0 This Week
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  • 4
    fastNLP

    fastNLP

    fastNLP: A Modularized and Extensible NLP Framework

    ... (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). Trainer provides a variety of built-in Callback functions to facilitate experiment recording, exception capture, etc. Automatic download of some datasets and pre-trained models.
    Downloads: 0 This Week
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