Fine-Tuning Pipelines
End-to-end LoRA and QLoRA fine-tuning pipelines on Llama 3, Mistral, Gemma — with dataset curation, synthetic data generation, and before/after benchmarking.
From domain-specific fine-tuning and RLHF alignment to production deployment and evaluation frameworks — we help you build LLMs that outperform generic models on your specific use case.
What We Build
End-to-end LoRA and QLoRA fine-tuning pipelines on Llama 3, Mistral, Gemma — with dataset curation, synthetic data generation, and before/after benchmarking.
Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO) to align models with your organization's values, tone, and quality standards.
Custom evaluation harnesses measuring hallucination rate, factual accuracy, toxicity, bias, and task-specific performance — with automated regression testing for every model update.
Ready to build?
Book a free 30-minute consultation to discuss your use case and get a custom roadmap.