Fine-Tuning LLMs
Fine-tune Llama, Mistral, and GPT models for specialized tasks. LoRA, QLoRA, PEFT, dataset preparation, evaluation, and deployment on real hardware.
or $230 lifetime $799
- Access to all 12 courses
- All future updates
- Certificate of completion
- 30-day money-back guarantee
About This Course
Fine-tuning is how you make a general-purpose LLM a specialist. This course covers the complete fine-tuning workflow: dataset curation and formatting, training with LoRA and QLoRA for efficiency, evaluating trained models, and deploying them to production. You'll work with Llama 3, Mistral 7B, and the OpenAI fine-tuning API on real tasks like domain-specific question answering, style transfer, and function calling.
What You'll Learn
- Decide when fine-tuning is worth it vs. prompting or RAG
- Curate and format high-quality training datasets for any task
- Fine-tune Llama 3 and Mistral with LoRA for efficient training
- Apply QLoRA to fine-tune on consumer hardware (single A100)
- Use the Hugging Face ecosystem fluently: Transformers, PEFT, TRL
- Track experiments with Weights & Biases
- Evaluate fine-tuned models rigorously with held-out test sets
- Deploy fine-tuned models with vLLM for production serving
Who Is This For?
Ready to move beyond prompting APIs to customize model behavior for specific domains
Need practical fine-tuning skills to test hypotheses and publish results
Building specialized AI tools in legal, medical, scientific, or other technical fields
Prerequisites
- Understanding LLMs
- Python for AI
- Basic familiarity with PyTorch helpful