Tutorials

What Tutorials Covers

This Tutorials archive brings together explainers, guides, and working examples on Python, Tutorial, Openai, Ollama, Local LLM, and LLMS. Learn by doing with step-by-step tutorials, hands-on projects, and practical implementations. Build real AI applications with working code examples.

Use this page when you want a solid starting point, a short list of strong next reads, or a quicker way to compare related ideas before you open a more specific article.

• Python 9
• Tutorial 7
• Openai 6
• Ollama 2
• Local LLM 2
• LLMS 2

Best Starting Points in Tutorials

If you are new to this topic, start with Run Local Coding Models on Mac with VS Code, Dual-GPU Setup for Local LLMs: Hardware & Parallelism Guide, and How to Create a Small Language Model from Scratch: Architecture, Training & Deployment. Together, those articles give you a clear overview, a few practical examples, and a better sense of where to go next.

• Run Local Coding Models on Mac with VS Code

  Set up a private local coding assistant in VS Code on Mac. Configure Ollama with Continue and Cline, dual-model autocomplete, and Qwen 2.5 Coder.

• Dual-GPU Setup for Local LLMs: Hardware & Parallelism Guide

  Learn how to build a dual-GPU setup for local LLMs. Configure PCIe bifurcation, power supply sizing, llama.cpp layer splitting, and vLLM tensor parallelism.

• How to Create a Small Language Model from Scratch: Architecture, Training & Deployment

  Master how to build, train, and deploy a small language model from scratch. Explore GQA, RoPE, synthetic data pipelines, PyTorch code, and GGUF quantization.