FreeCodeCamp - Building LLMs from Scratch

Google Colab for those who don't have a GPU: https://colab.research.google.com/drive/1_7TNpEEl8xjHlr9JzKbK5AuDKXwAkHqj?usp=sharing

• Will provide Chinese localization, further code comments, and programming practices.
• 将提供汉化和进一步代码注释和编程实践

Dependencies (assuming windows): pip install pylzma numpy ipykernel jupyter torch --index-url https://download.pytorch.org/whl/cu118

If you don't have an NVIDIA GPU, then the device parameter will default to 'cpu' since device = 'cuda' if torch.cuda.is_available() else 'cpu'. If device is defaulting to 'cpu' that is fine, you will just experience slower runtimes.

All the links you should need are in this repo. I will add detailed explanations as questions and issues are posted.

Visual Studio 2022 (for lzma compression algo) - https://visualstudio.microsoft.com/downloads/

OpenWebText Download - https://skylion007.github.io/OpenWebTextCorpus/

Socials

Twitter / X - https://twitter.com/elliotarledge

My YouTube Channel - https://www.youtube.com/channel/UCjlt_l6MIdxi4KoxuMjhYxg

How to SSH from Mac to Windows - https://www.youtube.com/watch?v=7hBeAb6WyIg&t=

How to Setup Jupyter Notebooks in 5 minutes or less - https://www.youtube.com/watch?v=eLmweqU5VBA&t=

Linkedin - https://www.linkedin.com/in/elliot-arledge-a392b7243/

Join My Discord Server - https://discord.gg/pV7ByF9VNm

Research Papers:

Attention is All You Need - https://arxiv.org/pdf/1706.03762.pdf

A Survey of LLMs - https://arxiv.org/pdf/2303.18223.pdf

QLoRA: Efficient Finetuning of Quantized LLMs - https://arxiv.org/pdf/2305.14314.pdf