Showing 5 open source projects for "rest api"

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    Kener

    Kener

    Kener is a Modern Self hosted Status Page, batteries included

    Kener: Open-source Node.js status page tool, designed to make service monitoring and incident handling a breeze. It offers a sleek and user-friendly interface that simplifies tracking service outages and improves how we communicate during incidents. And the best part? Kener integrates seamlessly with GitHub, making incident management a team effort—making it easier for us to track and fix issues together in a collaborative and friendly environment.
    Downloads: 1 This Week
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  • 2
    Haystack

    Haystack

    Haystack is an open source NLP framework to interact with your data

    Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning,...
    Downloads: 4 This Week
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  • 3
    API-for-Open-LLM

    API-for-Open-LLM

    Openai style api for open large language models

    API-for-Open-LLM is a lightweight API server designed for deploying and serving open large language models (LLMs), offering a simple way to integrate LLMs into applications.
    Downloads: 1 This Week
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  • 4
    Parsr

    Parsr

    Transforms PDF, Documents and Images into Enriched Structured Data

    Parsr is an open-source document parsing tool that converts PDFs, scanned images, and other structured documents into structured, machine-readable data formats.
    Downloads: 0 This Week
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  • 5
    NLP Best Practices

    NLP Best Practices

    Natural Language Processing Best Practices & Examples

    In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive business adoption of artificial intelligence (AI) solutions. In the last few years, researchers have been applying newer deep learning methods to NLP. Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. This repository contains examples and...
    Downloads: 0 This Week
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