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Summarization-Text (5 results) showing 1 - 5



Text Summarizer solution is an optimal way to tackle the problem of information overload by reducing the size of long documents into a few sentences . Neural-network-based models have the ability to automatically learn the distributed representation for sentences and documents. This summarizer is...

Model Package - Fulfilled on Amazon SageMaker


High performance production-ready Natural Language Processing API based on spaCy and HuggingFace transformers, for: - Entity extraction (NER) - Sentiment-analysis - Text classification - Summarization - Text generation (with GPT Neo 2.7B, the open-source equivalent of OpenAI GPT-3) - Question...


This solution helps users automate the coherent summary generation from documents. It identifies frequently used entity clusters in the document to capture salient and most important candidate sentences. An abstractive summary is generated from these sentences using reinforcement learning to...

Model Package - Fulfilled on Amazon SageMaker


Mphasis Knowledge Graph is a novel approach of summarizing or converting unstructured data into query-able triplets of Subject-Predicate-Object using NLP. It helps in semantic understanding of the unstructured data. The algorithm takes English text data as input and generates two outputs, the...

Model Package - Fulfilled on Amazon SageMaker


Natural Language Question Generator can be used to generate questions from free text content in scenarios such as educational content, conversational systems like chatbots, virtual assistants, FAQ creation etc. This solution leverages attention based models to generate appropriate questions from...

Model Package - Fulfilled on Amazon SageMaker

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