Neuron Explorer

Qwen3-0.6B

end of document boundary token

A neuron in layer 14 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 lights up at the invisible marker that signals one web page or document has ended and another begins. It is mostly quiet on ordinary words. Turning it up made the model's writing drift into unrelated, rambling topics.

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

    this video with your parents, friends, and/or adults and ask them if they can solve the problem as well⏎*Inspired by the movie Good Will Hunting<|endoftext|>Keats was one of the most life-loving people you could hope to meet,

  2. #2 peak

    .⏎The source code (with examples) is here: hideinfo.cpp.⏎This software comes with no warrantee of any sort, use at your own risk!<|endoftext|>Mind Ransomware is one of those infections that are supposedly released for “educ

  3. #3 peak

    1⏎By the end of Tuesday 16th please upload your piece ‘On D’ onto Moodle. Lots of dynamics and effects and different textures please!<|endoftext|>WOLFRAM SYSTEM MODELER⏎This

  4. #4 peak

    00 training examples, you can choose to pick 100 random samples (batch size=100) for each EPOCH (Training cycle)<|endoftext|>|Origin:||co

  5. #5 peak

    that is made terrible by our own mad attempt to interpret it as though it had⏎an underlying truth."⏎-- Umberto Eco⏎More information about the Python-list<|endoftext|>Jayne Davis: “I am not convinced in my area of research there are

  6. #6 peak

    .⏎Download or subscribe to this show at https://twit.tv/shows/triangulation.⏎Thanks to Cachefly for the bandwidth for this show.<|endoftext|>The Scarlet Letter is an 1850 romantic work of fiction in a

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 concept of a highly detailed, complex, and highly advanced world in which there are no boundaries of the entire planet's spatial complexity, and the entire world of the 22000 level of human civilization has been determined to 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

    FLs). Installing one CFL saves $15 annually, according to the Rocky Mountain Institute, a nonprofit energy research group. Multiply that by the number of lamps and fixtures in your home, and watch the savings add up. Some people also prefer

  2. #2 peak

    more likely.⏎Many scientists believe that the combination of a hereditary susceptibility to cancer and an environmental trigger, such as exposure to a carcinogen or being obese, puts individuals at risk of developing cancer, especially at an earlier adult age.<|endoftext|>Found

  3. #3 peak

    . The wholesalers and distributors took those inflated orders at face value and, erring on the side of caution, ordered even more appliances. Those seemingly small decisions added up to big problems for General Electric.⏎Forrester’s system dynamics perspective has helped

  4. #4 peak

    www.healthscout.com/template.asp?id=669525<|endoftext|>It is certain, in any case, that ignorance, allied with power, is the most ferocious enemy justice can have.⏎– James Baldwin⏎Four decades of neoliberal

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. L13:789 suppresses
  2. L12:144 suppresses
  3. L13:2738 suppresses
  4. L13:1489 excites
  5. L7:1112 excites
  6. L12:2212 suppresses 'to' or 'for' opening a purpose phrase
  7. L12:1947 suppresses
  8. L10:743 excites 'therefore' or 'thus' after a subject
  9. L8:1958 suppresses
  10. L5:2546 excites
  11. L12:1432 weakly excites
  12. L12:2968 weakly excites
  13. L13:2816 weakly suppresses
  14. L10:721 weakly suppresses
  15. L13:237 weakly suppresses
  16. L13:1727 weakly excites
  17. L13:359 weakly suppresses
  18. L11:2066 weakly suppresses
  19. L12:2683 weakly excites
  20. L8:401 weakly suppresses
  21. L13:149 weakly excites
  22. L7:480 weakly suppresses
  23. L13:1339 weakly suppresses
  24. L10:248 weakly suppresses

Feeds later layers

  1. L15:2215 suppresses
  2. L16:2080 weakly excites
  3. L16:2728 weakly suppresses
  4. L16:2635 weakly excites
  5. L18:2900 weakly suppresses
  6. L23:1378 weakly suppresses
  7. L16:80 weakly excites
  8. L17:2315 weakly suppresses
  9. L17:2685 weakly suppresses
  10. L21:1785 weakly excites
  11. L19:1681 weakly suppresses
  12. L15:1046 weakly excites
  13. L17:2873 weakly excites
  14. L17:2951 weakly suppresses
  15. L16:2874 weakly excites
  16. L15:2474 weakly suppresses
  17. L19:2705 weakly suppresses
  18. L19:2896 weakly suppresses
  19. L16:1256 weakly excites
  20. L16:2197 weakly suppresses
  21. L22:1806 weakly suppresses "to" introducing a purpose clause
  22. L18:1635 weakly excites
  23. L25:1223 weakly suppresses
  24. L24:90 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 -1.31 and -1.221 values between -1.22 and -1.131 values between -1.03 and -0.943 values between -0.94 and -0.854 values between -0.85 and -0.769 values between -0.76 and -0.6713 values between -0.67 and -0.588 values between -0.58 and -0.4923 values between -0.49 and -0.4046 values between -0.40 and -0.31104 values between -0.31 and -0.22227 values between -0.22 and -0.13626 values between -0.13 and -0.031774 values between -0.03 and 0.06547 values between 0.06 and 0.15239 values between 0.15 and 0.24108 values between 0.24 and 0.3370 values between 0.33 and 0.4237 values between 0.42 and 0.5128 values between 0.51 and 0.6011 values between 0.60 and 0.697 values between 0.69 and 0.784 values between 0.78 and 0.881 values between 0.88 and 0.971 values between 0.97 and 1.062 values between 1.06 and 1.151 values between 1.15 and 1.245 values between 1.24 and 1.332 values between 1.33 and 1.421 values between 1.42 and 1.511 values between 1.60 and 1.691 values between 1.69 and 1.791 values between 1.79 and 1.881 values between 2.24 and 2.33offnegativepositiveoften

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. inis
  2. .MiddleRight
  3. ise
  4. ru
  5. joined
  6. either
  7. 前后
  8. rus
  9. REPORT
  10. side

Suppresses

  1. amiento
  2. imiento
  3. ển
  4. edom
  5. Comprehensive
  6. aje
  7. 了解更多
  8. 对我来说
  9. oki
  10. iciente