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Tutorials

Tutorials

Hands-on deployment guides for AI frameworks, tools, and pipelines on dedicated GPU servers. Set up PyTorch, TensorFlow, vLLM, and more from scratch — full root access on bare metal.

Tutorials May 2026

vLLM Setup on the RTX 5060 Ti 16 GB: The Optimal Config

The vLLM launch flags that actually matter on a 16 GB Blackwell card — tuned for the memory ceiling and…

Tutorials May 2026

Prefix Caching on the RTX 5060 Ti 16 GB: 50% Free Throughput

vLLM's prefix caching is the single biggest free throughput win on small GPUs. Here is what it buys on a…

Tutorials May 2026

Self-Hosted RAG Evaluation Pipeline: Recall, Precision, Answer Quality

How to measure if your RAG stack is actually working — retrieval recall, reranker precision, and end-to-end answer quality with…

Tutorials May 2026

Self-Hosted AI Incident Postmortem Template

A practical postmortem template for AI inference incidents — root cause categories, action items, and what to track between incidents.

Tutorials May 2026

Self-Hosted LLM Evaluation Pipeline: Eval Harness, Custom Benchmarks, Regression Detection

How to evaluate open-weight LLMs on your specific workload — lm-evaluation-harness, custom test sets, and a CI pipeline that catches…

Tutorials May 2026

Self-Hosted LLM Fine-Tuning Pipeline: Data, Training, Eval, Deploy

End-to-end fine-tuning pipeline on dedicated GPU hardware — data prep, training run management, evaluation, and merging back for deployment.

Tutorials May 2026

AI Chatbot Streaming Architecture: From Browser to GPU and Back

End-to-end streaming chatbot architecture — browser to API gateway to vLLM and back, with the fragility points that bite in…

Tutorials May 2026

RTX 5060 Ti 16 GB RAG Stack Install in Under an Hour

The complete install recipe for a working RAG stack on a freshly-provisioned RTX 5060 Ti server. Llama 3.1, BGE, Qdrant,…

Tutorials May 2026

SFT vs DPO vs ORPO: Fine-Tuning Methods Compared in 2026

Three popular fine-tuning paradigms — supervised fine-tuning, direct preference optimisation, odds ratio preference optimisation. When each one wins.

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