SLM Playbook

Prerequisite: Review the previous module in the slm-playbook series before proceeding. ← Series hub Next → Answer-first: Self-hosting Small Language Models (2B–14B) with Go hybrid routing and vLLM serving reduces enterprise API costs by up to 65%, eliminates PII privacy risks, and delivers specialized domain performance matching 100B+ models. Implementing this architecture enforces sub-50ms P99 latency guarantees, strict component isolation, and automated observability pipelines required for production-grade enterprise operations. For the past two years, enterprise AI adoption has been dominated by a singular architectural pattern: API integration with massive, closed-source models (Frontier LLMs). While this API-Centric model allows for rapid prototyping, it becomes a severe liability when scaled to production workloads handling sensitive company data. ...

Prerequisite: Familiarity with the concepts introduced in Executive Summary. Review it first if the terminology in this part is unfamiliar. ← Series hub ← Previous | Next → Answer-first: Supervised Fine-Tuning (SFT) data quality determines downstream model capabilities; applying NEFTune noise injection during training improves conversational quality by up to 20%, while SemDeDup vector clustering prunes 30%–50% of redundant data to cut GPU training hours nearly in half without losing model accuracy. Implementing this architecture enforces sub-50ms P99 latency guarantees, strict component isolation, and automated observability pipelines required for. ...

Prerequisite: Familiarity with the concepts introduced in Part 2 — Sft Data Engineering. Review it first if the terminology in this part is unfamiliar. Answer-first: QLoRA fine-tuning combines 4-bit NormalFloat (NF4) base model quantization with low-rank adapter matrices ($r=16, \alpha=32$), reducing VRAM usage from 80GB to under 10GB and accelerating training speed by 4.5x using Unsloth Triton kernels on a single GPU. Adopting this pattern guarantees sub-50ms P99 latency bounds, zero-allocation memory optimization, and fault-tolerant event-driven state synchronization across production systems. ...