Neuron Explorer

Qwen3-0.6B

colon introducing a summary point

A neuron in layer 6 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 on a colon that introduces the main point or example after a sentence like "one thing in common:" or "a surprising discovery:". Turning it up made the text wander into unrelated topics, so the steering doesn't show the same idea.

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

    working women everywhere. The figures represent women of different races and celebrate the contributions made by women throughout time.⏎“Women all over the world have one trait in common: they work, they work hard, and their work is unheralded.”⏎

  2. #2 peak

    on the cover of the print edition.⏎Dysprosium is not only the atomic element with the strongest magnetic moments, but it also possesses another interesting property: its magnetic moments point either all the same direction (ferromagnetism) or

  3. #3 peak

    out slowly near the trunk, but not on<|endoftext|>Electric cars may be energy efficient Earth-saving futuremobiles, but their rise could also have a strange unintended consequence: killing off the oldest form of radio.⏎Two popular electric cars, the BMW i

  4. #4 peak

    using an online image generator.⏎This wasn’t the only piece of misinformation shared during and immediately after the terrorist attack. However, the majority had one thing in common: a visual element. Rarely were stories shared exclusively in text

  5. #5 peak

    , scientists have made a surprising discovery: a gigantic aquifer of relatively fresh water trapped in porous sediments lying below the

  6. #6 peak

    10 metres).⏎Aside from a few small streams and artificial lakes, Johannesburg lacks water. The city owes its location to the presence of an even more precious resource: gold. The city grew on the edge of the Witwatersrand Main Reef,

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: In the first paragraph, I have been thinking about the following points: 1. The first paragraph is about the following points: - The first paragraph is about the following points: - The first paragraph is about the following points: - 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

    strap on our virtual reality goggles, and hit the weights.⏎Researchers from the University of Wisconsin-Madison are doing something like that (although, of course, the weights don't weigh anything) by creating

  2. #2 peak

    a common food source for many Native American tribes including but not limited to the Iroquois, Algonquin, Ojibwa, and

  3. #3 peak

    of Cardiology: FDA Releases Final Regulation Extending Authority Over E-Cigarettes, Other Tobacco Products<|endoftext|>The aim of the project - which is in the style of a Wikipedia - is to make the large volume of

  4. #4 peak

    in the State of Ju”. This story was consolidated into this 4-character idiom and has the original meaning of not forgetting the humble past and in a place like China where the history is considered the backbone of its civilization (all through Chinese history

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. L5:2364 suppresses
  2. L5:194 weakly excites 'a' or 'of' right after a verb
  3. L5:1014 weakly excites
  4. L5:167 weakly excites
  5. L4:606 weakly excites
  6. L5:1534 weakly excites
  7. L4:1610 weakly excites
  8. L4:740 weakly suppresses
  9. L5:2819 weakly suppresses
  10. L5:543 weakly excites
  11. L2:34 weakly suppresses
  12. L5:1800 weakly excites
  13. L1:2847 weakly excites
  14. L0:2158 weakly excites
  15. L1:2818 weakly excites
  16. L4:929 weakly suppresses
  17. L3:1681 weakly suppresses "which" after a noun of "the X of which"
  18. L3:741 weakly suppresses
  19. L4:131 weakly excites
  20. L5:676 weakly excites
  21. L5:1021 weakly suppresses
  22. L3:2771 weakly excites
  23. L5:2256 weakly excites
  24. L1:1461 weakly excites

Feeds later layers

  1. L8:712 excites
  2. L17:2788 excites
  3. L7:582 excites
  4. L14:1491 excites word just before an example or elaboration
  5. L7:79 excites
  6. L16:2297 excites
  7. L14:2930 excites 'is' after a topic noun phrase
  8. L15:2787 excites
  9. L11:821 excites
  10. L11:1605 excites
  11. L11:1072 excites
  12. L12:837 excites
  13. L8:1608 excites
  14. L16:1041 excites
  15. L18:2350 weakly suppresses
  16. L14:1953 weakly excites
  17. L13:838 weakly excites
  18. L15:93 weakly suppresses
  19. L10:1208 weakly excites
  20. L17:2564 weakly excites
  21. L9:1083 weakly excites
  22. L14:2022 weakly excites
  23. L13:2996 weakly suppresses
  24. L11:865 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 -1.72 and -1.621 values between -1.53 and -1.441 values between -1.26 and -1.172 values between -1.17 and -1.083 values between -0.99 and -0.902 values between -0.90 and -0.801 values between -0.80 and -0.716 values between -0.71 and -0.625 values between -0.62 and -0.5336 values between -0.53 and -0.4450 values between -0.44 and -0.35151 values between -0.35 and -0.26349 values between -0.26 and -0.17750 values between -0.17 and -0.081256 values between -0.08 and 0.02777 values between 0.02 and 0.11319 values between 0.11 and 0.20128 values between 0.20 and 0.2929 values between 0.29 and 0.3814 values between 0.38 and 0.479 values between 0.47 and 0.562 values between 0.56 and 0.654 values between 0.65 and 0.752 values between 0.75 and 0.841 values between 0.84 and 0.933 values between 1.02 and 1.111 values between 1.11 and 1.201 values between 1.47 and 1.572 values between 1.57 and 1.662 values between 1.84 and 1.93offnegativepositiveoften

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. 那就是
  2. ippers
  3. latina
  4. 竟是
  5. theirs
  6. 材
  7. デン
  8. iox
  9. しまう
  10. mites

Suppresses

  1. paque
  2. 乱
  3. bart
  4. rey
  5. osaur
  6. 如有侵权
  7. .gc
  8. 未经
  9. 亂
  10. erà