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 27, 2024 - Jupyter Notebook