Neuron Explorer

Qwen3-0.6B

unclear: document boundary tokens

A neuron in layer 7 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron is weak and hard to pin down. Its strongest responses fall on the invisible end-of-document marker where one web page joins another, plus a few random words. Turning it up gave unrelated text, so there is no clear story here.

Written by Claude from this neuron's activations and steering outputs. Confidence: low. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    :<|endoftext|>Copyright © University of Cambridge. All rights reserved.⏎'Aim High' printed from

  2. #2 peak

    :<|endoftext|>The hamstring muscles – the biceps femoris, semitendinosus,

  3. #3 peak

    0 International<|endoftext|>POWER IN AC CIRCUITS⏎Power of a circuit is defined as the

  4. #4 peak

    compost in a<|endoftext|>In the Middle East and North Africa (MENA), women have made progress toward

  5. #5 peak

    Louisiana back to France (1800). U.S.A. purchases Louisiana (1

  6. #6 peak

    0 mph)<|endoftext|>Today I wondered which NT books relied more heavily on the Septuagint vs

Steering

Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.

turned down a lot
Prompt

Here is something I have been thinking about lately: the number of, and the number of, and the number of, and the number of, and the number of, and the number of, and the number of, and the number of, and the number of, and the number of

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    send, (and hopefully, receive), a valentine.⏎In the 1840

  2. #2 peak

    xA4;⏎P0 = 0xB0;⏎P0 = 0x99;⏎P0

  3. #3 peak

    easy as with other programming languages.⏎To create a list of integers, create a new variable and:⏎That’s simple right? And that wasn’t possible with Record Lists.⏎Creating a list of a single compound type like Entity or Structure, was

  4. #4 peak

    table with a specific name or index exists.⏎The following example retrieves a single table by name from the DataTableCollection.⏎Private Sub GetTableByName() ' Presuming a DataGrid is displaying more than one

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L3:385 suppresses
  2. L5:1007 suppresses
  3. L2:635 suppresses
  4. L5:164 suppresses
  5. L3:119 suppresses
  6. L3:377 suppresses
  7. L3:685 suppresses
  8. L3:228 excites
  9. L5:693 weakly suppresses
  10. L4:1918 weakly suppresses
  11. L4:1 weakly excites
  12. L4:19 weakly suppresses
  13. L3:437 weakly suppresses
  14. L5:2270 weakly excites
  15. L1:280 weakly excites
  16. L3:2076 weakly excites
  17. L2:1982 weakly suppresses
  18. L5:398 weakly excites
  19. L5:176 weakly suppresses
  20. L2:779 weakly excites
  21. L5:169 weakly excites
  22. L1:148 weakly suppresses
  23. L2:448 weakly excites
  24. L2:2774 weakly suppresses

Feeds later layers

  1. L9:110 excites
  2. L17:848 excites
  3. L10:1020 weakly excites
  4. L12:1242 weakly excites
  5. L15:544 weakly excites
  6. L18:467 weakly excites
  7. L25:554 weakly excites
  8. L8:1803 weakly suppresses
  9. L21:2839 weakly suppresses
  10. L21:1483 weakly suppresses
  11. L21:2420 weakly excites
  12. L23:106 weakly excites
  13. L16:444 weakly excites
  14. L21:2318 weakly excites
  15. L11:2573 weakly suppresses
  16. L13:1449 weakly excites
  17. L22:2325 weakly excites
  18. L19:1497 weakly suppresses
  19. L22:3066 weakly suppresses
  20. L23:937 weakly excites
  21. L12:1689 weakly excites
  22. L14:2239 weakly suppresses
  23. L10:914 weakly excites
  24. L8:426 weakly suppresses

Activation histogram

How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.

2 values between -1.44 and -1.361 values between -1.18 and -1.092 values between -1.00 and -0.911 values between -0.91 and -0.832 values between -0.83 and -0.741 values between -0.74 and -0.653 values between -0.65 and -0.567 values between -0.56 and -0.4729 values between -0.47 and -0.3841 values between -0.38 and -0.30140 values between -0.30 and -0.21351 values between -0.21 and -0.12736 values between -0.12 and -0.031157 values between -0.03 and 0.06803 values between 0.06 and 0.15401 values between 0.15 and 0.23160 values between 0.23 and 0.3244 values between 0.32 and 0.4115 values between 0.41 and 0.504 values between 0.50 and 0.593 values between 0.59 and 0.682 values between 0.68 and 0.771 values between 1.03 and 1.121 values between 1.12 and 1.211 values between 2.00 and 2.09offnegativepositiveoften

Logit lens

The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layers instead.

Promotes

  1. ermo
  2. being
  3. 有两个
  4. 政府采购
  5. PR
  6. 亚军
  7. rado
  8. ndon
  9. 照
  10. гос

Suppresses

  1. queryInterface
  2. HING
  3. .HttpContext
  4. .createTextNode
  5. ��
  6. oup
  7. 此文
  8. klä
  9. OCK
  10. ensions