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Source channel @githubtrending · Post #14815 · Jun 10

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm

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@githubtrending · Post #15412 · 01/14/2026, 04:30 PM

#jinja#ansible#ansible_collection#collection#devsec#hacktoberfest#hardening#linux#mysql_hardening#nginx#nginx_hardening#os_hardening#playbook#protection#role#ssh_hardening#sysctl devsec.hardening is an Ansible collection that battle-tests security hardening for Linux (CentOS, AlmaLinux, Rocky, Debian, Ubuntu, etc.), MySQL, Nginx, and SSH, matching DevSec Inspec baselines. Install via `ansible-galaxy collection install devsec.hardening` and apply roles like os_hardening easily. It saves you time by automating secure configs across servers, cuts manual work, boosts compliance, and shrinks attack surfaces for safer systems. https://github.com/dev-sec/ansible-collection-hardening