Neuron Explorer

Qwen3-0.6B

the word 'how' after 'find out' or 'learn'

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 on the word 'how' when it follows phrases like 'find out', 'learn' or 'advice on', where a 'how to' explanation is about to begin. Turning it up did not produce any clear theme in the model's replies.

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

    Wiki is a web-based, multi-lingual and interactive project - this means we need your input to ensure the pages are kept up to date. Find out how to contribute below.⏎Please note that this project is still being tested, if you

  2. #2 peak

    using published reference books, provides⏎rhymes, synonyms, antonyms, definitions, related words and more for⏎virtually every word. Even includes examples of how the word was used⏎in Shakespeare’s works.⏎Wordsmyth: The Educational

  3. #3 peak

    , and replaced H. cervicornis⏎as the species most often found attached or entangled on the upper branches<|endoftext|>This site is entirely user-supported. See how you can help.⏎We don't

  4. #4 peak

    available here.⏎Learn how activist judges are changing the culture of America and what We the People can do to

  5. #5 peak

    other ideas you'd like to contribute, we'd love to hear from you.⏎Find the latest in professional publications, learn new techniques and strategies, and find out how you can connect with other literacy professionals.⏎Teacher Resources by Grade⏎|1st

  6. #6 peak

    but have trouble with questions that ask them to identify the main point of a written passage. Our Veritas Prep professional instructors are able to provide students with techniques on how to improve specific skills tested in the Verbal Reasoning section.⏎Put Tips and

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 first time I saw the first 1551355555553555553555535555355555355553

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

    implemented as the brains of the entire operation. However, the Makers realized that an RPi would be a much better suitor for the job. After all, the sophisticated cube solving algorithms required quite a bit of memory — more than the Arduino

  2. #2 peak

    have the same life cycle, nesting areas, and impact on humans.⏎The primary thing that differentiates the tropical bed bug from the common bed bug is their habitat. While the common<|endoftext|>448 pp., 6.125 x

  3. #3 peak

    is that the IC rated fixtures can be buried in insulation and the non-IC rated fixtures cannot be covered or in contact with insulation. The reason for this is because the non-IC rated fixtures do not have the temperature rating to handle the heat

  4. #4 peak

    pile. This is because it takes a very long time for the bacteria that eats dog waste (and its nutrients) to be broken down. To make things worse, you can’t just add a few drops of dog waste to

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. L16:797 excites
  2. L14:1128 excites
  3. L10:1449 suppresses
  4. L14:1142 excites
  5. L16:943 excites
  6. L16:1652 excites
  7. L14:655 excites
  8. L14:531 suppresses
  9. L14:1891 excites
  10. L17:1282 excites
  11. L15:2971 suppresses
  12. L16:817 weakly suppresses
  13. L14:3051 weakly suppresses
  14. L11:2954 weakly excites
  15. L15:1702 weakly excites
  16. L16:1219 weakly excites
  17. L8:361 weakly excites
  18. L17:165 weakly suppresses
  19. L17:2397 weakly excites
  20. L17:58 weakly suppresses
  21. L15:975 weakly suppresses
  22. L16:1697 weakly suppresses
  23. L17:689 weakly excites
  24. L16:1112 weakly suppresses

Feeds later layers

  1. L19:1881 suppresses
  2. L20:599 suppresses
  3. L20:544 suppresses
  4. L19:766 suppresses
  5. L19:958 suppresses
  6. L19:638 suppresses
  7. L19:947 excites
  8. L20:1112 suppresses
  9. L20:955 suppresses
  10. L19:1854 suppresses
  11. L20:482 suppresses
  12. L20:1278 weakly suppresses
  13. L20:708 weakly suppresses
  14. L19:1434 weakly suppresses
  15. L20:1835 weakly suppresses
  16. L19:270 weakly suppresses
  17. L20:1233 weakly suppresses
  18. L20:1615 weakly suppresses
  19. L20:884 weakly suppresses
  20. L22:834 weakly suppresses
  21. L19:1080 weakly excites
  22. L22:189 weakly suppresses
  23. L19:2372 weakly suppresses
  24. L19:2118 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 -14.36 and -13.851 values between -11.31 and -10.801 values between -9.27 and -8.761 values between -8.76 and -8.253 values between -6.73 and -6.223 values between -6.22 and -5.712 values between -5.71 and -5.207 values between -5.20 and -4.695 values between -4.69 and -4.187 values between -4.18 and -3.6811 values between -3.68 and -3.1717 values between -3.17 and -2.6618 values between -2.66 and -2.1521 values between -2.15 and -1.6435 values between -1.64 and -1.1372 values between -1.13 and -0.621124 values between -0.62 and -0.112360 values between -0.11 and 0.40150 values between 0.40 and 0.9035 values between 0.90 and 1.4112 values between 1.41 and 1.9211 values between 1.92 and 2.437 values between 2.43 and 2.941 values between 2.94 and 3.452 values between 3.45 and 3.961 values between 5.48 and 5.99offnegativepositiveoften

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. ary
  2. ten
  3. ely
  4. angen
  5. 非常的
  6. even
  7. eri
  8. 但是我
  9. anity
  10. .SQL

Suppresses

  1. ilda
  2. uckle
  3. (Collection
  4. (ArrayList
  5. Illuminate
  6. each
  7. 淘宝
  8. mainland
  9. köp
  10. 階