The course equips developers with techniques to enhance the reliability of LLMs, focusing on evaluation, prompt engineering, and fine-tuning. Learn to systematically improve model accuracy through hands-on projects, including building a text-to-SQL agent and applying advanced fine-tuning methods.
lora evaluation-framework performance-optimization text-to-sql self-reflection mome prompt-engineering llm-accuracy instruction-fine-tuning memory-tuning iterative-fine-tuning llama-models model-reliability
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Updated
Aug 29, 2024 - Jupyter Notebook