Development

Redmine Time Tracker – Chrome Extension

A Chrome Extension with Vue.js to efficiently track time for Redmine tickets. #Setup Page # Issues Page # Search Results Features Steps to Use the Extension https://github.com/kzorluoglu/kedmine-chrome#steps-to-use-the-extension New Feature – 16.10.2023 New Feature – 16.10.2023 CSV to Redmine Table Converter Views: 59

3D Printing / Helm / Kubernetes / Server / Ubuntu

Octoprint via Helm and Kubernetes

This repository contains Helm chart configurations for deploying OctoPrint project. The setup.sh script allows you to easily configure and deploy the chart. Direct Repo address for those with Kubernetes and Helm knowledge: https://github.com/kzorluoglu/octoprint-helm Prerequisites – Helm v3.x– Kubernetes cluster– Bash shell Usage Clone the Repository Run the Setup Script First, make the script executable: Then, run the script: The script will prompt you for the following information: These values will be used to populate the config.yaml file, which will be used for the Helm installation. Helm Install The script will automatically run helm install with the provided project name and config.yaml file. […]

Development / Linux / Server / Ubuntu

MJPG-streamer installation and run at System Startup using Systemd – Ubuntu Server

mjpg-streamer is a popular tool for streaming MJPEG video from webcams. In this tutorial, we will learn how to configure mjpg-streamer to run automatically at system startup using a systemd service unit file. Installation via Snap Step 1: Create the Service Unit File In the text editor, paste the following content: [Unit] Description=MJPG Streamer After=network.target [Service] ExecStart=ExecStart=mjpg-streamer -i “input_uvc.so” -o “output_http.so -w /home/kzorluoglu/charts/octoprint/www” Restart=always [Install] WantedBy=multi-user.target Step 2: Enable and Start the Service BONUS: if you want to run mjpg-streamer without sudo, you can try the following steps. Add your user to the video group: sudo usermod -aG video <your_username> […]

AI / Development / PHP

AI Model Trainer with EleutherAI/gpt-j-6b for Chameleon Shop Codes

The Trainer use actually the best chatgpt alternative model on huggingface. Here is the Training notice from Original Source: This model was trained for 402 billion tokens over 383,500 steps on TPU v3-256 pod. It was trained as an autoregressive language model, using cross-entropy loss to maximize the likelihood of predicting the next token correctly. https://huggingface.co/EleutherAI/gpt-j-6b#training-procedure Dataset Links: https://d8devs.com/chameleon-base-and-chameleon-shop-datasets-20230530-1918/ Views: 61