Showing 2 open source projects for "run time java"

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  • Unimus makes Network Automation and Configuration Management easy. Icon
    Unimus makes Network Automation and Configuration Management easy.

    Deploying Unimus to manage your entire network requires only minutes, allowing for rapid deployment without headaches.

    We aim to make automation, disaster recovery, change management and configuration auditing painless and affordable for a network of any size.
    Learn More
  • Ango Hub | All-in-one data labeling platform Icon
    Ango Hub | All-in-one data labeling platform

    For AI teams and Computer Vision team in organizations of all size

    AI-Assisted features of the Ango Hub will automate your AI data workflows to improve data labeling efficiency and model RLHF, all while allowing domain experts to focus on providing high-quality data.
    Learn More
  • 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
    Last Update:
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