πŸ“š Bibliography: LLMs and Tokenization

Large Language Models Fundamentals

ResourceType/FocusLanguageAccess
Hugging Face NLP CourseComplete course on NLP and transformersENOnline
Wikipedia: Large language modelIntroduction to LLMs, history and applicationsENOnline
OpenAI: GPT-3 PaperTechnical paper on GPT-3ENarXiv
Vaswani et al. (2017). "Attention Is All You Need"Seminal paper on Transformer architectureENarXiv

Tokenization and BPE

ResourceType/FocusLanguageAccess
Hugging Face: Byte-Pair Encoding tokenizationDetailed BPE tutorial with implementationENOnline
Wikipedia: Byte pair encodingHistory and operation of BPE algorithmENOnline
Sennrich, R., Haddow, B., & Birch, A. (2016). "Neural Machine Translation of Rare Words with Subword Units"Original paper on BPE for NLPENarXiv
Hugging Face TokenizersTokenizers library documentationENOnline

Transformers and Architectures

ResourceType/FocusLanguageAccess
The Illustrated TransformerVisual explanation of Transformer architectureENOnline
Attention Is All You NeedOriginal Transformers paper (Google)ENarXiv
Stanford CS224N: Natural Language Processing with Deep LearningStanford course on NLPENOnline
Devlin, J. et al. (2018). "BERT: Pre-training of Deep Bidirectional Transformers"BERT paperENarXiv

Pre-trained Models and Fine-tuning

ResourceType/FocusLanguageAccess
Hugging Face Model HubRepository of pre-trained modelsENOnline
OpenAI API DocumentationGPT-3.5/4 documentationENOnline
Radford, A. et al. (2019). "Language Models are Unsupervised Multitask Learners"GPT-2 paperENPDF
Brown, T. et al. (2020). "Language Models are Few-Shot Learners"GPT-3 paperENarXiv

Medical Applications of LLMs

ResourceType/FocusLanguageAccess
Nature: Large language models in medicineLLM applications in medicineENArticle
PubMed: ChatGPT and HealthcareReview on ChatGPT in healthcareENArticle
Med-PaLM: Google's Medical LLMMedical-specialized LLMENarXiv
WHO: Ethics and governance of AI for healthWHO ethical perspective on AI in healthENPDF

Note: All links have been verified and are accessible online. arXiv articles are freely available. For journal articles, check your university library or Google Scholar.