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Course overview: Understanding LLMs
01 Introduction
Background
Sheet 1.1: Practical set-up & Training data
02 ANNs & RNNs
PyTorch, ANNs & LMs
Sheet 2.1: PyTorch essentials
Sheet 2.2: ML-estimation
Sheet 2.3: Non-linear regression (MLP w/ PyTorch modules)
Sheet 2.4: Character-level sequence modeling w/ RNNs
Sheet 2.5: Introduction to HuggingFace & LMs
03 LSTMs & transformers
LSTMs & Transformers
Sheet 3.1: Tokenization & Transformers
Sheet 3.2: Transformer configurations & Training utilities
Prompting & Current LMs
Sheet 3.3: Prompting & Decoding
Homework
Homework 1: Language models (50 points)
Homework 2: Prompting & Generation with LMs (50 points)
Repository
Open issue
Index