Geek Out Time: Where LLMs “Keep” Their Facts? (VSCode with Colab)
A few weeks ago, we tried “ Reducing Hallucination with DoLa in Google Colab (Microsoft Phi-2)”( https:// nedvedyang.medium.com/geek-out-time-reducing-hallucination-with-dola-in-google-colab-microsoft-phi-2-ec878793df50 ) , a technique that improves factual accuracy by mixing signals from different transformer layers. It sparked some very interesting questions from the folks, one of which kept coming back:
“So… does this mean the lower layers of an LLM are actually more factual?”
We’re going to see the layers in action, using the new Google Colab integration inside VS Code released a few days ago . ( https://developers.googleblog.com/en/google-colab-is-coming-to-vs-code/ )
We run some deeper experiments, and clarify what’s really happening inside a modern 7B model.
This is an excerpt — the full article continues on Medium.
Read the full article on Medium →Related Posts
- Geek Out Time: The Economics of LLMs -How Token Pricing Quietly Shapes the ArchitectureDec 2025
- Geek Out Time: Demystifying vLLM’s KV Cache, Latency & Context Isolation for Faster LLMsJun 2025
- Ctrl+Alt+Delete My Career? A Veteran Developer's Take on How LLMs Are Changing Software EngineeringJun 2025
- Geek Out Time: Understanding Inference-Time Reasoning in LLMs with Google Colab and NVIDIA NIMMay 2025