Large language models (LLMs)
- Natural Language Processing
- Natural language understanding
- Capacities
- Capacity
- Similarity to humans - see also Personas
- Domain-specific
- Impact
- Models
- Tools
- Training
- Persona
- Visualization
Overview
Language model implemented with huge Neural networks.
Neural language models perform the language modeling tasks by using a neural network rather than explicitly estimating the conditional probabilities, by learning good vector-space representations for words, sentences, etc.
Issues
Large language models are often called Stochastic parrot, given that they are simply models that predict the next (or missing) token one by one. One exemplary problem from this is that large language models often confidently lie.
They can suffer from Training data leakage and memorization in language models.
Topics
Models
Tutorials and reviews
- Intro to Large Language Models by Andrej Karpathy
- Understanding Large Language Models by Sebastian Raschka
- Large language models, explained with a minimum of math and jargon
- Anti-hype LLM reading list
- Developing an LLM: Building, Training, Finetuning by Sebastian Raschka
- Generative AI from scratch by Graphics in 5 Minutes
From scratch
- https://github.com/rasbt/LLMs-from-scratch by Sebastian Raschka
- Let’s build GPT: from scratch, in code, spelled out by Andrej Karpathy
- https://github.com/karpathy/llm.c
- Create a Large Language Model from Scratch with Python free code camp
Text generation
Memes
https://yyiki.s3.amazonaws.com/public/imgs/gromit_LLM_nextword.mp4