Search Results for "amp stack"
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Showing 6 open source projects for "amp stack"
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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MAMP Stack Manager
Control Apache, MySQL, and PHP services
Control Apache, MySQL, and PHP services on MacOS. Services must be installed using Homebrew. -
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WebServer / AMP Stack for Windows
WebServer (AMP Stack) for Windows. Support multiple PHP versions.
WebServer (AMP Stack) for Windows. Support multiple PHP versions. - Software: Apache, MySQL, MariaDB, MongoDB. - Multiple PHP Versions. - Apache supports HTTPS. - Can install on External Disk, it will fix the config path for you. - Auto-create hosts file entry for the website. - Manage servers as Windows services. - Manage websites with different PHP versions -
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A portable AMP stack for web developers.
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Personal AMP - Apache, MySQL and PHP - stack for the S60 mobile phone. For installation and other information, please follow the 'Project Web Site' link to the right, or Project->Website from the menu.
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AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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XAMPLE creates a separate, encrypted and independent LAMP environment on a system that does or does not already run a web server and database. It is useful to provide a customized environment for software refusing to work with the installed LAMP stack.
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Mellum-4b-base
JetBrains’ 4B parameter code model for completions
...Built with 4 billion parameters and a LLaMA-style architecture, it was trained on over 4.2 trillion tokens across multiple programming languages, including datasets such as The Stack, StarCoder, and CommitPack. With a context window of 8,192 tokens, it excels at code completion, fill-in-the-middle tasks, and intelligent code suggestions for professional developer tools and IDEs. The model is efficient for both cloud inference with vLLM and local deployment using llama.cpp or Ollama, thanks to its bf16 precision and AMP training. ...
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