General information
Lecturer: Flavio Giobergia
Co-lecturer: Riccardo Coppola
π Mondays
π£ 8:30 β 11:30 (3h)
π Room 19A
π Wednesdays
π¦ 11:30 β 13:00 (1.5h)
π Room 9S
Course material
LLM Foundations
- Introduction to Language Models
- Introduction to deep learning
- Word embeddings
- Recurrent Neural Networks
- Transformers
- LLM 1 – A brief histort of LLMs
- LLM 2 – Metrics, Tasks, Benchmarks
- LLM 3 – Instruction tuning and model alignment
- LLM 4 – Efficient fine-tuning and inference
Other material
- GitHub repository (link)
News
- 28/10/2024 – Uploaded LLM4 slides, lab 04 text+solution (GitHub)
- 21/10/2024 – Uploaded LLM2/3, labs 02/03 (GitHub)
- 14/10/2024 – Uploaded LLM1 slides, lab 01 text+solutions (GitHub)
- 09/10/2024 – Uploaded an updated version of the Transformers slides
- 30/09/2024 – Uploaded Transformers slides
- 28/09/2024 – Uploaded lab 01’s solution (GitHub), Word embeddings, Recurrent Neural Networks
- 23/09/2024 – Uploaded lab 01’s text (GitHub)
- 22/09/2024 – Uploaded Intro to Language models, Intro to deep learning