List of things I want to pick up at some time:

• <Insert here>
• Sparse AutoEncoder Explainability (https://adamkarvonen.github.io/machine_learning/2024/06/11/sae-intuitions.html)
• The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs >> MUST READ!
• 30 Papers (ilya)
• Top papers in LLMs + Top ViT papers
• https://x.com/youraimarketer/status/1778992208697258152 >> Cited By Karpathy as good
• https://github.com/karpathy/LLM101n → We can use this structure
• https://www.youtube.com/@umarjamilai
• https://huggingface.co/docs/transformers/main/en/quantization/overview