FINE TUNING LLM's and LLM BASICS COVERED IN THIS PROJECT

Google Colab can be used for those who don't have a GPU:

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.

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

Fine Tuning LLM Research Papers Reference:

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

https://towardsdatascience.com/fine-tuning-large-language-models-llms-23473d763b91 - This is a very good reference