Neuron Explorer

Qwen3-0.6B

document boundary separator token

A neuron in layer 18 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 fires most strongly on the hidden marker that separates one web page from the next in the training text, right where an abrupt change of topic happens. Its negative side is code and listings. Turning it up or down gave odd, loose text with no clear theme.

Written by Claude from this neuron's activations and steering outputs. Confidence: medium. 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

    00<|endoftext|>The reasons and urgency that lead a group of people to just up and leave a

  2. #2 peak

    that<|endoftext|>After splitting genetically from wolves about 135,000 years ago

  3. #3 peak

    requires a bit better understanding of color<|endoftext|>ORLANDO, Florida — The curse of the mummy may truly be fatal

  4. #4 peak

    environmentally incompatible.<|endoftext|>Dhyunsar Mahadev Temple is a major Hindu temple located in the

  5. #5 peak

    needed around planes en route to keep them safely separated.<|endoftext|>FEDERAL Hill House is a squat building in central Providence, within earshot

  6. #6 peak

    rounded to the nearest integer.<|endoftext|>Christine Duncan, MD⏎Sickle cell disease (SCD) affects as

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 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

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

    :⏎void * memchr ( const void *, int, size_t );⏎instead of the two overloaded versions provided in C++.⏎/* memchr example */⏎int main ()⏎char * pch;⏎char str = "Example string";⏎pch = (char

  2. #2 peak

    ⏎> 2 if n> 10⏎> 3 print "This might take a while..."⏎> 4 for i = 1 to n⏎> 5 for j = 1 to i⏎> 6 print

  3. #3 peak

    anyway :P)⏎void genFactorial(int x, int t)⏎int total = t; // you probably wouldn't even need total now⏎void main(void) //<|endoftext|>Splattered Plants Should Serve As A Reminder⏎By Phran Novelli

  4. #4 peak

    a sacred religious ceremony, in South Dakota this past summer.⏎Complete information about survivors could not be confirmed<|endoftext|>A simple example of HTML is:⏎<HTML> <HEAD> <TITLE>This is the Title</TITLE> </HEAD> <BODY

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. L14:67 suppresses
  2. L15:500 excites
  3. L6:429 excites
  4. L17:432 weakly excites
  5. L16:211 weakly suppresses
  6. L1:746 weakly excites
  7. L17:95 weakly suppresses
  8. L1:79 weakly excites
  9. L8:2262 weakly suppresses
  10. L16:180 weakly suppresses
  11. L6:296 weakly excites
  12. L9:11 weakly suppresses
  13. L1:2635 weakly suppresses
  14. L8:27 weakly excites
  15. L10:2098 weakly suppresses
  16. L13:1578 weakly suppresses
  17. L14:1840 weakly suppresses
  18. L17:31 weakly suppresses
  19. L14:57 weakly suppresses
  20. L2:1250 weakly suppresses
  21. L10:1124 weakly suppresses
  22. L2:587 weakly suppresses
  23. L14:2840 weakly excites
  24. L15:274 weakly suppresses

Feeds later layers

  1. L21:441 suppresses
  2. L20:656 weakly suppresses
  3. L19:2457 weakly suppresses
  4. L19:1516 weakly suppresses
  5. L25:144 weakly excites
  6. L21:229 weakly suppresses
  7. L23:205 weakly excites
  8. L23:1310 weakly excites
  9. L19:163 weakly suppresses
  10. L21:367 weakly suppresses
  11. L20:378 weakly excites
  12. L23:740 weakly excites 'well' in well-dressed, well-known, well-off
  13. L25:209 weakly suppresses
  14. L23:558 weakly excites
  15. L19:2290 weakly suppresses
  16. L20:1301 weakly suppresses
  17. L27:502 weakly suppresses
  18. L19:1157 weakly suppresses
  19. L26:145 weakly excites
  20. L21:282 weakly excites
  21. L20:1795 weakly suppresses
  22. L24:2694 weakly suppresses
  23. L19:2079 weakly suppresses
  24. L27:256 weakly excites

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.

1 values between -6.65 and -6.012 values between -4.72 and -4.082 values between -4.08 and -3.442 values between -3.44 and -2.795 values between -2.79 and -2.154 values between -2.15 and -1.5115 values between -1.51 and -0.86557 values between -0.86 and -0.223202 values between -0.22 and 0.4274 values between 0.42 and 1.0716 values between 1.07 and 1.716 values between 1.71 and 2.356 values between 2.35 and 2.995 values between 2.99 and 3.642 values between 4.92 and 5.562 values between 6.85 and 7.491 values between 7.49 and 8.141 values between 8.78 and 9.421 values between 9.42 and 10.061 values between 10.06 and 10.711 values between 13.28 and 13.921 values between 13.92 and 14.561 values between 18.42 and 19.06offnegativepositiveoften

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. iskey
  2. 副校长
  3. uerdo
  4. 的道路
  5. setMax
  6. congregation
  7. patible
  8. aker
  9. recipient
  10. 招呼

Suppresses

  1. olate
  2. ……
  3. …)
  4. …)⏎⏎
  5. …”
  6. ,…⏎⏎
  7. 意思
  8. ..."); ⏎
  9. …"
  10. \")