RAG vs. Fine-Tuning: Choosing the Right Strategy for Your Data
Should you retrain the model or give it a textbook? We break down when to use RAG vs. Fine-Tuning (or both) for enterprise AI.
LLM Finetuning
Preparing Your Enterprise Data for LLM Training
Garbage in, garbage out. The success of your custom LLM depends entirely on the quality of your training dataset. Here is the blueprint.
Fine-Tuning Llama 3 for Domain-Specific Enterprise Tasks
Generic models are powerful, but domain experts are better. Learn how to fine-tune Llama 3 on your internal documents to create a specialised AI.
Evaluating Fine-Grained Performance in Custom LLMs
How do you know your model is 'good'? Moving beyond loss curves to semantic evaluation frameworks and 'LLM-as-a-Judge'.
Efficient PEFT Techniques: LoRA and QLoRA Explained
Training a 70B parameter model was once impossible for most. Low-Rank Adaptation (LoRA) changes the game, enabling training on consumer GPUs.
