LLM Fine-tuning

I help you fine-tune large language models for domain specificity, higher accuracy, and better alignment with your product goals. This includes instruction tuning, preference tuning, and task-specific adaptation for both open-source and proprietary models.

What you’ll get:

1. Dataset strategy (instruction, conversational, preference, or synthetic)
2. Fine-tuning approach selection (SFT, LoRA, QLoRA, adapters, full FT)
3. Training setup (compute, batching, token efficiency)
4. Evaluation & failure analysis (hallucinations, regressions, bias)
5. Deployment-ready checkpoints

Best for:

SaaS products, internal copilots, domain-specific chatbots, research teams.