#702 · Primary category： Education & Research
Transformers-for-NLP-2nd-Edition
Comprehensive guide to transformer models from BERT to GPT-4, with hands-on fine-tuning, training, and prompt engineering examples.
Project last updated：01/04/24
GitHub Stars
966
Forks
362
Contributors
2
License
MIT
Why we included this project
Anyone working through the second edition of Denis Rothman's transformer book will find this repository a solid companion. It is a teaching resource rather than a deployable service, and the Jupyter notebooks mirror the book's chapters, moving from BERT attention heads and positional encodings to RoBERTa pretraining and fine-tuning. The later material and the Dolphin bonus examples show how to shift older workflows onto OpenAI's chat completions and GPT-4 APIs, with notes on breaking changes like model renames and the client pattern, and they include DALL-E image generation and Google Cloud AI examples. Notebooks ship with launch links for cloud services that come preinstalled with CUDA, so you can skip local GPU setup. Keep in mind that much of the content reflects the OpenAI ecosystem as of early 2024.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
JavaGuide
Java Interview & Backend General Interview Guide, covering computer fundamentals, databases, distributed systems, high concurrency, system design, and AI application development.
system-prompts-and-models-of-ai-tools
A curated collection of system prompts, internal tools, and AI models from popular AI assistants and coding agents.
30-seconds-of-code
Coding articles to level up your development skills
generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI