home.social

#developement — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #developement, aggregated by home.social.

  1. I started a big _big_ BIG refactoring of my pet project and... holy crap, I am rewriting most of it.

    But that's a learning process, right? I am getting a clearer and clearer image of how to build what I wanna build, and am slowly (very slowly) getting there, I suppose...

    #rust #rustland #developement #softwaredevelopment #floss #opensource #opensourcesoftware

  2. Making the most out of a small LLM

    Yesterday i finally built my own #AI #server. I had a spare #Nvidia RTX 2070 with 8GB of #VRAM laying around and wanted to do this for a long time.

    The problem is that most #LLMs need a lot of VRAM and i don't want to buy another #GPU just to host my own AI. Then i came across #gemma3 and #qwen3. Both of these are amazing #quantized models with stunning reasoning given that they need so less resources.

    I chose huihui_ai/qwen3-abliterated:14b since it supports #deepthinking, #toolcalling and is pretty unrestricted. After some testing i noticed that the 8b model performs even better than the 14b variant with drastically better performance. I can't make out any quality loss there to be honest. The 14b model sneaked in chinese characters into the response very often. The 8b model on the other hand doesn't.

    Now i've got a very fast model with amazing reasoning (even in German) and tool calling support. The only thing left to improve is knowledge. #Firecrawl is a great tool for #webscraping and as soon as i implemented websearching, the setup was complete. At least i thought it was.

    I want to make the most out of this LLM and therefore my next step is to implement a basic #webserver that exposes the same #API #endpoints as #ollama so that everywhere ollama is supported, i can point it to my python script instead. This way it feels like the model is way more capable than it actually is. I can use these advanced features everywhere without being bound to it's actual knowledge.

    To improve this setup even more i will likely switch to a #mixture_of_experts architecture soon. This project is a lot of fun and i can't wait to integrate it into my homelab.

    #homelab #selfhosting #privacy #ai #llm #largelanguagemodels #coding #developement

  3. Making the most out of a small LLM

    Yesterday i finally built my own #AI #server. I had a spare #Nvidia RTX 2070 with 8GB of #VRAM laying around and wanted to do this for a long time.

    The problem is that most #LLMs need a lot of VRAM and i don't want to buy another #GPU just to host my own AI. Then i came across #gemma3 and #qwen3. Both of these are amazing #quantized models with stunning reasoning given that they need so less resources.

    I chose huihui_ai/qwen3-abliterated:14b since it supports #deepthinking, #toolcalling and is pretty unrestricted. After some testing i noticed that the 8b model performs even better than the 14b variant with drastically better performance. I can't make out any quality loss there to be honest. The 14b model sneaked in chinese characters into the response very often. The 8b model on the other hand doesn't.

    Now i've got a very fast model with amazing reasoning (even in German) and tool calling support. The only thing left to improve is knowledge. #Firecrawl is a great tool for #webscraping and as soon as i implemented websearching, the setup was complete. At least i thought it was.

    I want to make the most out of this LLM and therefore my next step is to implement a basic #webserver that exposes the same #API #endpoints as #ollama so that everywhere ollama is supported, i can point it to my python script instead. This way it feels like the model is way more capable than it actually is. I can use these advanced features everywhere without being bound to it's actual knowledge.

    To improve this setup even more i will likely switch to a #mixture_of_experts architecture soon. This project is a lot of fun and i can't wait to integrate it into my homelab.

    #homelab #selfhosting #privacy #ai #llm #largelanguagemodels #coding #developement

  4. Making the most out of a small LLM

    Yesterday i finally built my own #AI #server. I had a spare #Nvidia RTX 2070 with 8GB of #VRAM laying around and wanted to do this for a long time.

    The problem is that most #LLMs need a lot of VRAM and i don't want to buy another #GPU just to host my own AI. Then i came across #gemma3 and #qwen3. Both of these are amazing #quantized models with stunning reasoning given that they need so less resources.

    I chose huihui_ai/qwen3-abliterated:14b since it supports #deepthinking, #toolcalling and is pretty unrestricted. After some testing i noticed that the 8b model performs even better than the 14b variant with drastically better performance. I can't make out any quality loss there to be honest. The 14b model sneaked in chinese characters into the response very often. The 8b model on the other hand doesn't.

    Now i've got a very fast model with amazing reasoning (even in German) and tool calling support. The only thing left to improve is knowledge. #Firecrawl is a great tool for #webscraping and as soon as i implemented websearching, the setup was complete. At least i thought it was.

    I want to make the most out of this LLM and therefore my next step is to implement a basic #webserver that exposes the same #API #endpoints as #ollama so that everywhere ollama is supported, i can point it to my python script instead. This way it feels like the model is way more capable than it actually is. I can use these advanced features everywhere without being bound to it's actual knowledge.

    To improve this setup even more i will likely switch to a #mixture_of_experts architecture soon. This project is a lot of fun and i can't wait to integrate it into my homelab.

    #homelab #selfhosting #privacy #ai #llm #largelanguagemodels #coding #developement

  5. Making the most out of a small LLM

    Yesterday i finally built my own #AI #server. I had a spare #Nvidia RTX 2070 with 8GB of #VRAM laying around and wanted to do this for a long time.

    The problem is that most #LLMs need a lot of VRAM and i don't want to buy another #GPU just to host my own AI. Then i came across #gemma3 and #qwen3. Both of these are amazing #quantized models with stunning reasoning given that they need so less resources.

    I chose huihui_ai/qwen3-abliterated:14b since it supports #deepthinking, #toolcalling and is pretty unrestricted. After some testing i noticed that the 8b model performs even better than the 14b variant with drastically better performance. I can't make out any quality loss there to be honest. The 14b model sneaked in chinese characters into the response very often. The 8b model on the other hand doesn't.

    Now i've got a very fast model with amazing reasoning (even in German) and tool calling support. The only thing left to improve is knowledge. #Firecrawl is a great tool for #webscraping and as soon as i implemented websearching, the setup was complete. At least i thought it was.

    I want to make the most out of this LLM and therefore my next step is to implement a basic #webserver that exposes the same #API #endpoints as #ollama so that everywhere ollama is supported, i can point it to my python script instead. This way it feels like the model is way more capable than it actually is. I can use these advanced features everywhere without being bound to it's actual knowledge.

    To improve this setup even more i will likely switch to a #mixture_of_experts architecture soon. This project is a lot of fun and i can't wait to integrate it into my homelab.

    #homelab #selfhosting #privacy #ai #llm #largelanguagemodels #coding #developement

  6. Making the most out of a small LLM

    Yesterday i finally built my own #AI #server. I had a spare #Nvidia RTX 2070 with 8GB of #VRAM laying around and wanted to do this for a long time.

    The problem is that most #LLMs need a lot of VRAM and i don't want to buy another #GPU just to host my own AI. Then i came across #gemma3 and #qwen3. Both of these are amazing #quantized models with stunning reasoning given that they need so less resources.

    I chose huihui_ai/qwen3-abliterated:14b since it supports #deepthinking, #toolcalling and is pretty unrestricted. After some testing i noticed that the 8b model performs even better than the 14b variant with drastically better performance. I can't make out any quality loss there to be honest. The 14b model sneaked in chinese characters into the response very often. The 8b model on the other hand doesn't.

    Now i've got a very fast model with amazing reasoning (even in German) and tool calling support. The only thing left to improve is knowledge. #Firecrawl is a great tool for #webscraping and as soon as i implemented websearching, the setup was complete. At least i thought it was.

    I want to make the most out of this LLM and therefore my next step is to implement a basic #webserver that exposes the same #API #endpoints as #ollama so that everywhere ollama is supported, i can point it to my python script instead. This way it feels like the model is way more capable than it actually is. I can use these advanced features everywhere without being bound to it's actual knowledge.

    To improve this setup even more i will likely switch to a #mixture_of_experts architecture soon. This project is a lot of fun and i can't wait to integrate it into my homelab.

    #homelab #selfhosting #privacy #ai #llm #largelanguagemodels #coding #developement

  7. I made a small break from the #network monitor to focus on my #youtube #music downloader and if there's one thing i can say it's that youtube is fucked up. The same playlist can return different videos (which happens a lot of times). Also reliable metadata searching is a pain in the ass. For 100% reliable metadata searching you have to strip the video title down, remove any fragments that don't belong in the original title, normalize it and then compare it against a normalized, lowercase version of the metadata search result.

    #developement #coding #go #golang

  8. Today i've nearly finished the transition to #Vue.

    Next steps are adding more #API #endpoints, implementing the pages in the #frontend and finally #dockerizing and publishing it 🔥

    #coding #developement #docker #linux #sysadmin #selfhosting #homelab #homeserver #server

  9. I realized that i need to separate the #frontend and #backend. I'm glad i didn't do a lot of work on the frontend yet. I will probably go with #react. Since the dashboard will display a lot of informations, which must update live, a #uiframework becomes necessary.

    #developing #developement #coding #webdevelopment

  10. I made so much progress yesterday. I've completely restructured the #codebase, improved the #performance, added logging with loglevels, and worked a bit on the webui. I still have a lot of work to do, but the project is a lot of fun and i really want to realize this. Can't wait to release the first alpha version. Who knows, maybe this becomes a cool community project. It will be extensible and flexible, so that might be realistic.

    #coding #developement #go #security #homelab #selfhosting #opensource #freeandopensource

  11. This is just beautiful. The project uses #MariaDB to store all the collected data. It makes heavy use of #API endpoints which will be a top priority not only for the internal workings. My focus mostly lies in making this as flexible as possible so people can configure it exactly as they need it. Configuration will be in #yaml.

    What i got so far is:

    • packet capturing (from client, sent to the control server)
    • a webhook (which will be a drop-in replacement for #Discord's since a lot of services support sending logs to discord webhooks)

    What's planned:

    • Log file monitoring (like #Fail2Ban, but more advanced and easier to configure)
    • A fully featured dashboard which visualizes the data and gives you control and a transparent overview of your network activity.
    • IP banning (multiple ways to make it flexible)
    • Maybe even some advanced responses (like reporting all ports as open for nmap scans)

    I would be very interested to know what you think. Ideas, criticism and questions are very welcome. As soon as the base is working, i will push it to #Github.

    #developement #coding #sideproject #homelab #security #networking #monitoring #xdr

  12. Sol schrieb den folgenden Beitrag Sat, 15 Mar 2025 05:38:26 +0100

    Predicting What Comes After DeepSeek


    #Predicting What Comes After #DeepSeek #China
    Already we are seeing Chinese companies take a different approach to AI development from OpenAI, Meta, and Tesla. Rather than building a moat protected by high Capex investment, proprietary software and high profit margin, DeepSeek, Alibaba, Unitree and BYD are developing an ecosystem through open sourcing, engineering optimization, and free/low-cost software. The goal is to drive quick adoption, scale and fast iteration, thus achieving long term market share gains.

    #ai #developement #opensouce #technology
  13. Encore une très belle édition de l'opensource job fair organisée par @ulyssis 😎 Merci aux organisateurs et a tous les étudiants qui sont passés nous voir. #kul #ucl @ULBruxelles

    opensourcejobfair.be/

    #opensource #job hashtag#iam #worfklow hashtag#leuven #testing #developement

  14. A votre avis, pour trouver une entreprise qui respecte les #dev et les bonnes pratiques en 2025 il vaut mieux... (C'est pour un ami ;) ) #developement #php #rust #golang #craft

  15. Il Linux Day Milano del 26 ottobre si avvicina, e ora puoi consultare la scaletta completa dei talk qui: linuxdaymilano.org/schedule/. Preparati per una giornata di sessioni avanzate su Linux, software libero e tecnologie open source!
    Non vediamo l’ora di vederti lì!
    #LinuxDay #LinuxDayMilano #OpenSource #FreeSoftware #LinuxPower #FOSS #Linux #Kubernetes #Developement

  16. Alright... Diving deeper in the world of ROS. I see why many told me to look into it. Yikes!!!

    ros.org/

    #robotics #developement

  17. Want to iterate only the keys or only the values of 'std::map' or 'std::unordered_map' and you find `std::pair<>` ugly? Then this might be for you:

    moseleyinstruments.com/blog/ma

    #developement #cpp

  18. that was the story about my communication with the company i want to get on whose free trainings, and description of their online test, it has -1500 symbols to read, you can find it by selecting this replay. the hashtags: #android #programming #education #developement #software #communication hope thats enough

  19. Je viens juste de commencer le tuto #rust rust-book-fr/ch01-03-hello-cargo.
    Tout se passe bien mais... l'exécutable de la cible release fait 4.5 Mo... J'ai raté un truc ?? #foss #developement

  20. Was ist eigentlich DevOps?

    Es ist die Brücke zwischen Softwareentwicklung (Development) und Operations! Durch die Kombination können wir:
    🔥 Schnellere Software-Updates für agile Marktreaktionen liefern.
    💪 Eine stabilere Software durch frühzeitige Fehlererkennung garantieren.
    💰 Kosten durch Automatisierung und Überwachung sparen.

    Neugierig, wie DevOps Unternehmen voranbringen kann? 🌐
    Schreiben uns einfach: [email protected]

    #devops #opensource #software #developement #operations #solutions

  21. #Microsoft ist auf github mit einem Kleinbetrag Sponsor der #Mastodon gGmbh... Äh... lol? :-)

    Wer kann und möchte, kann sich dem illusteren Kreis anschließen. Lassen wir das MS-Logo in der Masse verschwinden ;-)

    Der Beitrag dort fließt in die Entwicklung von #Mastodon (der Software).

    github.com/sponsors/mastodon

    @Mastodon #mastodon #fundraiser #developement

  22. What do you prefer guys as backend framework?
    PS (Can't add more than 4 in the Poll)
    Other framework?
    Mention it below 👇🏻

    #backend #dev #web #webdev #database #API #programming #Developer #developement #hack #python #java #javascript #PHP

  23. I've just write something at writefreely.public.cat/kernuac I'm not a very good writer but sometimes I'll share with all of you some long texts there.

    Disclaimer: English is not my native language, I speak Spanish; Please forgive my mistakes.

    #writefreely #vim #vscode #devs #developer #developement #ssh #blog #blogs

  24. "A lively discussion is happening on the Gutenberg repository about renaming the Command Center. This new feature, designed to be an extensible quick search and command execution tool, was introduced in Gutenberg 15.6. In version 16.0, it came out of the experimental stage and its API is now public, ready for developers to create their own custom commands."

    wptavern.com/wordpress-contrib

    #WordPress #Developement #Website