| DATA | ARGOMENTO | MATERIALI |
|---|---|---|
| - | Prompting LLMs | - Slide - Everyday Prompting - Prompt Engineering Guide - 17 Prompting Techniques, Test them in Python - Top-K/Top-P/Temp. |
| - | LAB: Prompting LLM | - OpenAI ChatGPT - HF-Llama2-13b-chat - HF-Mistral-7B |
| - | Retrieval Augmented Generation | - Intro, Extended - Build |
| - | LLM Agents | - Slides, - LangChain Course |
| - | LLM dal 2017 al 2025 | - Link |
MATERIALI AGGIUNTIVI & CURIOSITA'
Where are facts stored in Large Language Models?
Reinforcement Learning from Human Feedback
How to Evaluate LLM Summarization.
Running DeepSeek R1 locally, ( Ollama )
Exactly How Much vRAM (and Which GPU) Can Serve Your LLM?