Neuron Explorer

Qwen3-0.6B

"have" or "take" after you or they

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 lights up on the verb right after a pronoun like "you" or "they", especially the word "have" (as in "you have to" or "you have more"). Turning it up did not produce any obvious change in the topic of the writing.

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

    more possibilities of surviving adverse environmental conditions. We have very extreme weather in the highlands, and if it gets very cold and you only have<|endoftext|>Poor communication in just one area can affect the entire health care experience.⏎F

  2. #2 peak

    you usually get access to a command line interpreter, or shell. This takes your input and runs programs for you. If you are familiar with DOS, you already have used a command line interpreter: the COMMAND.COM program. Under DOS, your shell

  3. #3 peak

    key step in the gemstone id process. By using the unaided eye and 10 power magnification to determine the visible characteristics you are able to take a large step in the right

  4. #4 peak

    is an unsupervised learning problem.⏎To illustrate this, predicting whether a person will default on a loan or not. For this, you have a target variable i.e. ‘defaulting on loan’, which is a supervised

  5. #5 peak

    8.5 lbs in Thailand and 15 lbs in Asia as a whole. The Burmese have traditionally snacked a lot because they have traditionally only had two meals a day—one at around 10:00am and another

  6. #6 peak

    time of less than one second to be excellent, less than 5 seconds to be good, and greater than 5 seconds to be poor.⏎Sometimes you also have to consider other metrics that don't have a direct impact on the user experience.

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: of course, the problem is of the fact that of course, with the ... and so on of, of course, with ... of, of course, of, of, and of, of, of, of, of, of,

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

    say that we're taking a tough stand against misbehavior, but the data say it simply hasn't been effective in improving student behavior or ensuring school safety."⏎Tell it to Congress. The Gun-Free Schools Act of 1994 mandates zero

  2. #2 peak

    scientific objectivity, universality, and rational deduction over other ways of knowing the world. (148) Cogito ergo sum: "I think

  3. #3 peak

    DRM protected ebook on your desktop or laptop you will need to have Adobe Digital Editions installed. It is a free software. We also strongly recommend that you sign up for an AdobeID at

  4. #4 peak

    aining things like headers, etc.⏎Upon success, if you set ``parse_xml_document=True``, this will⏎contain the parsed xml_document. I'll take care of parsing errors⏎with an appropriate pylons_response for you.⏎server_response

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. L16:1860 suppresses
  2. L14:1719 excites
  3. L10:668 suppresses
  4. L12:336 suppresses
  5. L17:1196 suppresses
  6. L17:2129 excites
  7. L9:2219 excites
  8. L14:526 suppresses
  9. L9:584 suppresses
  10. L8:1300 excites
  11. L14:1148 excites
  12. L3:110 weakly excites
  13. L11:2015 weakly suppresses
  14. L15:795 weakly excites
  15. L16:2655 weakly excites
  16. L4:2085 weakly excites
  17. L5:146 weakly excites
  18. L14:149 weakly suppresses
  19. L12:434 weakly suppresses
  20. L16:674 weakly excites
  21. L6:1114 weakly excites
  22. L13:1808 weakly excites
  23. L6:388 weakly excites
  24. L16:2128 weakly excites

Feeds later layers

  1. L24:1263 suppresses
  2. L19:1969 suppresses
  3. L24:424 suppresses
  4. L21:1441 weakly suppresses
  5. L20:645 weakly suppresses
  6. L19:1371 weakly excites
  7. L23:1814 weakly suppresses
  8. L23:984 weakly suppresses
  9. L22:823 weakly suppresses
  10. L22:2398 weakly suppresses
  11. L20:2338 weakly suppresses
  12. L22:205 weakly suppresses
  13. L20:1103 weakly excites
  14. L20:851 weakly excites
  15. L19:1150 weakly excites
  16. L19:385 weakly excites
  17. L22:1093 weakly excites
  18. L24:803 weakly suppresses
  19. L19:1482 weakly suppresses
  20. L26:2817 weakly suppresses
  21. L19:272 weakly suppresses
  22. L21:239 weakly excites
  23. L22:2530 weakly excites
  24. L23:312 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 -6.09 and -5.464 values between -5.46 and -4.832 values between -4.83 and -4.203 values between -4.20 and -3.577 values between -3.57 and -2.9424 values between -2.94 and -2.3141 values between -2.31 and -1.6867 values between -1.68 and -1.04272 values between -1.04 and -0.412481 values between -0.41 and 0.22628 values between 0.22 and 0.85113 values between 0.85 and 1.4854 values between 1.48 and 2.1155 values between 2.11 and 2.7434 values between 2.74 and 3.3817 values between 3.38 and 4.0114 values between 4.01 and 4.6413 values between 4.64 and 5.276 values between 5.27 and 5.9011 values between 5.90 and 6.5310 values between 6.53 and 7.169 values between 7.16 and 7.7910 values between 7.79 and 8.435 values between 8.43 and 9.066 values between 9.06 and 9.696 values between 9.69 and 10.321 values between 10.95 and 11.586 values between 11.58 and 12.211 values between 12.21 and 12.841 values between 13.48 and 14.112 values between 14.74 and 15.371 values between 16.00 and 16.632 values between 17.89 and 18.531 values between 18.53 and 19.16offnegativepositiveoften

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. ao
  2. oser
  3. 能在
  4. Taj
  5. ,在
  6. 不在
  7. 能够在
  8. uge
  9. 就在
  10. avoided

Suppresses

  1. aturing
  2. sağlamak
  3. proposing
  4. շ
  5. 疲劳
  6. offre
  7. abric
  8. atoria
  9. lectic
  10. -century