My Workflow for Understanding LLM Architectures

This article presents a structured workflow for understanding Large Language Model (LLM) architectures, particularly when encountering new open-weight model releases, to facilitate effective learning and analysis. By following this workflow, AI engineers can systematically dissect and comprehend the complexities of LLMs, enabling them to leverage these models more efficiently in their applications.

⚡ Key Takeaways

• The workflow involves initial model exploration to understand its capabilities and limitations.
• It includes a step for analyzing the model's architecture, focusing on its components and how they interact.
• The workflow also emphasizes the importance of experimenting with the model on various tasks to gain practical insights into its performance and potential applications.

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