Neuron Explorer

Qwen3-0.6B

words right before 'all' or 'in'

A neuron in layer 25 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. It is featured, so it has steering outputs.

What this neuron does

This neuron tends to light up on a word that is often followed by the small words 'all' or 'in', such as 'fill' before 'in' or 'comply' before 'all'. When it was turned up, the model kept writing the word 'all' over and over.

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

    The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.<|endoftext|>

  2. #2 peak

    have successfully created an account.⏎A verifications link was sent to your email at . Please check your email and click on the link to confirm your email address and fully activate your iCPALMS account. Please check your spam folder.<|endoftext|>W

  3. #3 peak

    ovsky Poland⏎Vladimir-Volynsk, Poland… Summer 1943 – Galina and Yuri

  4. #4 peak

    9 16 25.........⏎Basics: Divide integers to get integer outputs in all cases⏎Determine value using Look-up table method⏎Create Volcano (or Atoll) martix. It is an extension of Bullsey

  5. #5 peak

    license.⏎A protocol transfer⏎- You give up the ability to profit from your work.⏎- You transfer the rights indefinitely.⏎- You need to print, fill in

  6. #6 peak

    5000 copies and never went out of print.⏎This PDF is a full-text searchable reproduction of the entire issue of this publication with all images, including advertisements.⏎Gushee asks whether New Orleans deserves its central place

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: multiple life conditions, multiple life conditions, life conditions... just like life conditions... life conditions... life conditions... life conditions... life conditions... life conditions... life conditions... life conditions... life conditions... life conditions... life conditions... life conditions

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

    !⏎The Great Unknown: Risk-Taking Behavior in Adolescents⏎19.01.2017 | Max-Planck-Institut für Bildungsforschung⏎A sudden drop in outdoor temperature increases the risk of respiratory

  2. #2 peak

    solar system, and some scientists think that they hold a key to understanding how the planets formed and why they are so diverse. By studying Comet 67P/C-G, researchers think they might start to learn more about how comets formed in

  3. #3 peak

    the long-standing mysteries surrounding how a comet works as it flies near the sun.⏎Here are five strange facts about Rosetta's target, Comet 67P/C-G:⏎It's going to be harpooned⏎Rosetta has been traveling

  4. #4 peak

    carried out research into the kinds of scoliosis treatments available at the time Richard was alive.⏎They included looking at 11th century Persian polymath Avicenna's theories on using traction.⏎Avicenna also advocated the massage techniques pract

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. L23:1458 excites
  2. L15:59 weakly excites
  3. L19:1982 weakly suppresses
  4. L10:564 weakly excites
  5. L9:3013 weakly excites
  6. L7:92 weakly suppresses
  7. L0:1034 weakly suppresses
  8. L10:375 weakly suppresses
  9. L5:146 weakly excites
  10. L18:1601 weakly suppresses
  11. L1:2348 weakly excites
  12. L24:1373 weakly suppresses 'all' in 'all over the world'
  13. L19:1554 weakly suppresses
  14. L2:5 weakly excites
  15. L11:2164 weakly excites
  16. L16:2202 weakly excites
  17. L4:76 weakly suppresses
  18. L19:1305 weakly suppresses unclear: verbs after a noun or 'that'
  19. L0:2105 weakly excites
  20. L5:656 weakly excites
  21. L1:727 weakly suppresses
  22. L24:2705 weakly excites
  23. L4:2279 weakly excites
  24. L14:263 weakly suppresses

Feeds later layers

  1. L27:769 strongly excites
  2. L26:684 weakly excites
  3. L27:1781 weakly suppresses
  4. L27:668 weakly suppresses
  5. L27:667 weakly suppresses
  6. L27:1682 weakly suppresses
  7. L27:2249 weakly suppresses
  8. L26:890 weakly suppresses
  9. L27:1967 weakly suppresses
  10. L26:1685 weakly suppresses
  11. L27:1775 weakly suppresses
  12. L26:843 weakly suppresses
  13. L26:522 weakly suppresses
  14. L27:612 weakly excites
  15. L26:901 weakly suppresses
  16. L26:973 weakly suppresses
  17. L26:1810 weakly excites
  18. L26:2252 weakly suppresses
  19. L26:2502 weakly suppresses
  20. L27:273 weakly suppresses
  21. L27:2576 weakly suppresses capital N starting a name
  22. L27:2768 weakly suppresses
  23. L26:257 weakly suppresses
  24. L26:351 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.

2 values between -14.81 and -14.071 values between -14.07 and -13.341 values between -13.34 and -12.611 values between -12.61 and -11.883 values between -11.88 and -11.156 values between -11.15 and -10.412 values between -10.41 and -9.689 values between -9.68 and -8.9514 values between -8.95 and -8.2211 values between -8.22 and -7.4914 values between -7.49 and -6.7517 values between -6.75 and -6.0230 values between -6.02 and -5.2934 values between -5.29 and -4.5662 values between -4.56 and -3.8375 values between -3.83 and -3.10140 values between -3.10 and -2.36220 values between -2.36 and -1.63292 values between -1.63 and -0.90729 values between -0.90 and -0.171651 values between -0.17 and 0.56319 values between 0.56 and 1.3092 values between 1.30 and 2.0361 values between 2.03 and 2.7635 values between 2.76 and 3.4924 values between 3.49 and 4.2215 values between 4.22 and 4.9611 values between 4.96 and 5.698 values between 5.69 and 6.426 values between 6.42 and 7.158 values between 7.15 and 7.884 values between 7.88 and 8.613 values between 8.61 and 9.352 values between 9.35 and 10.084 values between 10.08 and 10.811 values between 11.54 and 12.271 values between 13.74 and 14.47offnegativepositiveoften

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. all
  2. all
  3. 所有
  4. (all
  5. .all
  6. _all
  7. →all
  8. All
  9. All
  10. ALL

Suppresses

  1. ляр
  2. multiple
  3. wygląda
  4. MULT
  5. ไหน
  6. agua
  7. 别的
  8. reement
  9. 火炬
  10. 那是