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