A complete walkthrough for fine-tuning DeepSeek distilled models (specifically DeepSeek-R1-Distill-Qwen-7B) for custom tasks using QLoRA and LoRA adapters. Covers dataset preparation in JSONL/ChatML format, 4-bit quantization setup, SFTTrainer configuration, evaluation against base model, and deployment via TGI Docker with a
Table of contents
How to Fine-Tune DeepSeek Models for Custom Use CasesTable of ContentsUnderstanding DeepSeek Models and Fine-Tuning ConceptsPreparing Your DatasetSetting Up the Training EnvironmentConfiguring and Running the Fine-Tuning JobEvaluating Your Fine-Tuned ModelServing the Fine-Tuned Model via Node.js APIBuilding a React Frontend for InteractionImplementation Checklist and Best PracticesWhere to Go from HereSort: