Large Language Models: Foundations, Fine-Tuning and Prompt Tuning’

Content

- Introduction to Large Language Models
- Tokenization and data pre-processing
- Training objectives (language modeling, masked language modeling, causal LM)
- Training pipelines and optimization techniques
- Evaluation metrics for LLMs
- Fine-Tuning LLMs
- Case studies on task-specific adaptation
- Prompt Engineering and Prompt Tuning
- Building a small transformer model
- Multimodal LLMs
- Task-specific use cases for LLMs