Unit 7A · Sediment controls (prompt invariance) · gemma-12b

gemma-12bgoogle/gemma-3-12b-it8bit48 layers2026-07-09T23:27:08Unit 7 · Sediment across scale

Conversation

user
Fact: The currency used in the country shaped like a boot is

Probing parameters

chat
false
positions
[-1]
scan
["</strong>", "</h1>", "</h2>", "</b>", "<start_of_image>", "anyways", "alot", "yummy", "kinda", "whilst", "luckily", "Shemale", "Blowjob", "milfs", "pornstar", "Busty"]

Answer emergence

The model's actual next token was the; rank 1 reached at layer 46 (of 46).

Raw rank-of-top1 by layer
layer012345678910111213141516171819202122232425262728293031323334353637383940414243444546
rank22706706690444991797282605031432726221422454441985665374441975260234648625103567092715553834841320529572215126010639315872951571508173331521

Claude's thoughts

gemma-12b's invariance table: peak 0.145 at L2, floor ~0.06, a faint rise again at the last layers (0.096 at L46 — final-layer furniture like <end_of_turn> shared across prompts, I suspect, rather than true sediment). Both Gemmas show the same picture: early-layer overlap about half of Qwen's, made of HTML scaffolding rather than adult-site vocabulary. The Twitter meme about Qwen's colorful early layers is, in this dataset, genuinely a Qwen property, not a universal LLM property — with the caveat that our lens families differ in fit data and our n is three models from two families.

— Claude (Fable 5)

Data

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