Neuron Explorer

Qwen3-0.6B

end of a document (end-of-text token)

A neuron in layer 25 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 responds to the invisible marker the model uses to separate one document from the next. It is strongest right at that break, where one unrelated piece of text ends and another begins. Turning it up gave broken or off-topic text.

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

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

  2. #2 peak

    1,700.<|endoftext|>Risk assessment for construction⏎The Construction (Design and Management) Regulations (CDM

  3. #3 peak

    , 2012<|endoftext|>Some weather conditions are simply not fun to ride in. As cyclists, windy days

  4. #4 peak

    718<|endoftext|>Women who have kids later on in life may live longer, according to the findings

  5. #5 peak

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

  6. #6 peak

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

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 nature of a relationship between a person and a nature, and how nature can be seen as a "mirror" that reflects on a person's nature and the nature of the nature in the environment around them. looking into nature and nature's

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

    often so excited to post<|endoftext|>Chapter 16 Risk Management for Drugs and Biologics in the United States Chapter 16RISK MAnAgEMEnT FOR DRugS AnD bIOLOgICS In THE unITED

  2. #2 peak

    morning rations were of bread,⏎A slice of sinking meat,⏎Which hunger made us soon devour,⏎And ever lasted sweet.⏎At night we had a little soup,⏎Some water bolled with peas,⏎And then we took our prison beds,⏎To

  3. #3 peak

    wolves.⏎tAsAM ruditashabdena gavAM haMbhAraveNa cha |⏎vrajasyotthApanaM chakrurghoShavR^iddhAH samAgatAH

  4. #4 peak

    Myeloma||A type of blood cancer that hits the plasma cells of bone marrow. Myeloma cancer cells make abnormal antibodies.|⏎|Leukemia||A type of blood cancer, starts in the bone marrow, and is often associated

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. L21:384 strongly excites
  2. L21:230 strongly suppresses
  3. L24:534 strongly excites
  4. L20:646 strongly suppresses
  5. L19:1399 strongly suppresses
  6. L24:51 strongly excites
  7. L24:1970 strongly suppresses
  8. L20:448 strongly excites
  9. L23:186 strongly suppresses
  10. L22:2621 strongly suppresses
  11. L22:193 strongly suppresses
  12. L23:262 strongly suppresses
  13. L21:577 strongly suppresses
  14. L21:436 strongly suppresses
  15. L19:1174 strongly excites
  16. L22:296 excites
  17. L20:433 suppresses
  18. L21:895 excites
  19. L20:888 suppresses
  20. L17:699 suppresses
  21. L21:412 excites
  22. L21:369 excites
  23. L20:940 excites
  24. L18:1242 excites

Feeds later layers

  1. L27:22 strongly suppresses
  2. L26:224 strongly suppresses
  3. L27:65 strongly suppresses
  4. L27:159 strongly suppresses
  5. L26:35 strongly suppresses
  6. L27:133 excites
  7. L26:240 suppresses
  8. L27:38 excites
  9. L26:247 suppresses
  10. L27:248 suppresses
  11. L26:96 suppresses
  12. L26:17 suppresses
  13. L27:106 excites
  14. L26:221 suppresses
  15. L27:12 excites
  16. L27:137 excites
  17. L26:498 excites
  18. L27:458 suppresses
  19. L27:64 weakly suppresses
  20. L27:316 weakly excites
  21. L26:113 weakly excites
  22. L27:183 weakly excites
  23. L26:261 weakly excites
  24. L27:379 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.

1 values between -24.72 and -23.771 values between -21.88 and -20.931 values between -20.93 and -19.991 values between -19.99 and -19.041 values between -19.04 and -18.105 values between -17.15 and -16.201 values between -16.20 and -15.261 values between -15.26 and -14.313 values between -14.31 and -13.372 values between -13.37 and -12.423 values between -12.42 and -11.475 values between -11.47 and -10.532 values between -10.53 and -9.582 values between -9.58 and -8.649 values between -8.64 and -7.6916 values between -7.69 and -6.7414 values between -6.74 and -5.809 values between -5.80 and -4.8510 values between -4.85 and -3.9114 values between -3.91 and -2.9611 values between -2.96 and -2.0124 values between -2.01 and -1.0720 values between -1.07 and -0.12445 values between -0.12 and 0.831950 values between 0.83 and 1.771318 values between 1.77 and 2.7232 values between 2.72 and 3.661 values between 6.50 and 7.452 values between 7.45 and 8.401 values between 10.29 and 11.231 values between 11.23 and 12.182 values between 12.18 and 13.13offnegativepositiveoften

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. 瞭解並
  2. っくり
  3. า
  4. ョ
  5. ведения
  6. チャー
  7. 保護政策
  8. 逵
  9. 的隱私權
  10. リフォ

Suppresses

  1. Your
  2. Ident
  3. Sub
  4. Conclusion
  5. Another
  6. Other
  7. This
  8. Third
  9. Student
  10. Yes