Showing 2 open source projects for "run time java"

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    Run applications fast and securely in a fully managed environment

    Cloud Run is a fully-managed compute platform that lets you run your code in a container directly on top of Google's scalable infrastructure.

    Run frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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  • Propel Software: Product Value Management Platform for Manufacturers Icon
    Propel Software: Product Value Management Platform for Manufacturers

    For modern product companies that need to connect product and commercial teams successfully

    Propel is a cloud-native Product Value Management platform that unifies PLM, QMS, and PIM in one connected system, giving manufacturers complete visibility and control across the entire product lifecycle. It provides a single source of truth for all product data, streamlines change management, strengthens quality and compliance processes, and accelerates time-to-market by eliminating the silos and manual steps that slow teams down.
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  • 1
    Email to Event - ETE

    Email to Event - ETE

    The python App/Skrypt automaticly add important events into calendar.

    ...*Email is using standart IMAP, Calendar use iCalendar API and authentification method. Fast setup: 1. Download and unpack 2. Install LM studio - recomended for GPU compute 3. Run run_setings.bat and set your authentificators for email***/calendar and etg. 4. Push button SAVE 5. Push button PLAN for add task to Time scheduler 6. Check by run run_ETE.bat **Model must understand your language, test before use! ***In emal seting(usualy on web) create a new folder and set auto COPY! More information and complete instalation guidein in READ ME file. ...
    Downloads: 0 This Week
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  • 2
    Acharya

    Acharya

    A Data Centric annotation tool for your Named Entity Recognition

    ...Setup an MLOps pipeline to experiment with different algorithms on the same data and increase their accuracy and performance in a data-centric way. Installation and Setup for Acharya are not required, Acharya runs the initial setup when run for the first time. Rapidly identify and fix labeling errors in your dataset. Import/export datasets in multiple formats, train a model and use it to aid in the annotation process. Setup an MLOps pipeline to experiment with different algorithms on the same data and increase their accuracy and performance in a data-centric way. Gain insights about your training & test data, distribution of annotated entities, and decide how to curate your data for better accuracy.
    Downloads: 0 This Week
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