Great post! The breakdown of scaling laws, especially the comparison between Kaplan et al.'s findings and the Chinchilla paper, is super insightful. Understanding the balance between model size, data, and compute is crucial for efficient LLM development.
Great post! The breakdown of scaling laws, especially the comparison between Kaplan et al.'s findings and the Chinchilla paper, is super insightful. Understanding the balance between model size, data, and compute is crucial for efficient LLM development.
Thanks for sharing the recommended reads as well.