Fine-tune Llama, Mistral, or any open-source LLM on your custom dataset in 2026. Step-by-step guide using QLoRA, PEFT, and HuggingFace Transformers. Train on a single GPU for under $10.
Strategies for updating LLMs with new data including knowledge cutoff solutions, fine-tuning approaches, elastic weight consolidation, experience replay, and RAG alternatives.
Fine-tune embeddings for specialized domains. Generate training pairs with LLMs, train with sentence-transformers, and deploy custom embedding models in production.