Neuron Explorer

Qwen3-0.6B

comma ending a clause before an action

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 a comma that comes right after a complete phrase, when a new action is about to follow, like 'picked it up, and went' or 'you woke up, and you tried'. When it was turned up, the model's text fell into repeating filler words like 'have, have, have'.

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

    unlearn” the response patterns that were prohibiting them from accepting the new cultural requirements. The consultant and top management identified the response patterns that were getting in the way, and those that were required by the organization to be able to quickly understand and embrace

  2. #2 peak

    heat stopped the bleeding.⏎Curiously, the Native Americans left Thompson’s scalp next to the knocked-out Englishman. After he came to, he picked it up, and went back to Omaha

  3. #3 peak

    data directory is included in the MySQL distribution:⏎MySQL Zip archive distributions for Windows contain an unmodified data directory. You can unpack such a distribution into a temporary location, then copy it⏎datadirectory to where you are setting up the new instance

  4. #4 peak

    don’t just study the instrument, and look at it, and answer questions about it, and figure out how notes go. You put the instrument in your hands, and there you go — you are a practitioner.⏎“You still have to have the

  5. #5 peak

    however, only works if you can brush your teeth, eat breakfast, and get ready for school. Let’s say one morning you woke up, and you tried to get dressed, but you couldn’t.⏎What if you woke

  6. #6 peak

    limitations. In particular, I think it assumes that the fomite route is that the virus starts on the hands of an infected person, is transferred to an object or surface, and then picked up on the hands of

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 number of the last two and the number of the first and second, and then the number of the second and third, and the number of the third, and the first and second, and then the number of the first and third,

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

    -in” methodology. It starts at the outside by identifying business outcomes, and then drills down into the feature set that will achieve those outcomes. Each feature is

  2. #2 peak

    a layer or layers, highlight the ones you want to duplicate in your timeline and hit Command D.⏎You can create a pre-composition by highlighting all your layers and hitting Shift Command C. What a pre-comp will do it merge all your layers

  3. #3 peak

    and collaborating with other data scientists. When you sign up, you get free access to Watson Studio and all other IBM services for 30 days. Start now and take advantage of this offer.⏎- Learn how it performs at speeds up to

  4. #4 peak

    to Roman numerals. The tool basically works on a very simple concept of format conversion. In other words you just have to fill in the value of Arabic numeral and it will show the same value in Roman numeral. You can convert any desired Arabic

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. L16:357 strongly suppresses
  2. L15:2643 strongly excites
  3. L17:2911 suppresses
  4. L15:1542 excites
  5. L17:2776 suppresses
  6. L15:1924 suppresses
  7. L16:2279 suppresses
  8. L16:2500 excites
  9. L16:1669 suppresses
  10. L14:1746 excites
  11. L15:1467 excites
  12. L17:173 suppresses opening bracket that adds a synonym
  13. L16:2247 suppresses
  14. L16:3014 suppresses
  15. L13:2929 excites
  16. L16:2880 suppresses
  17. L15:412 excites
  18. L14:1184 excites
  19. L16:2738 excites
  20. L16:774 suppresses
  21. L14:361 suppresses
  22. L17:585 excites
  23. L16:1528 excites
  24. L13:1066 weakly suppresses

Feeds later layers

  1. L19:492 strongly suppresses
  2. L19:1769 excites
  3. L26:236 excites
  4. L26:22 suppresses the 'res' fragment inside words
  5. L19:1089 excites
  6. L19:867 excites
  7. L20:1083 excites
  8. L27:286 excites
  9. L20:882 excites
  10. L24:216 excites
  11. L27:86 suppresses
  12. L19:845 excites
  13. L20:349 suppresses
  14. L24:199 suppresses
  15. L25:438 excites
  16. L20:1484 excites
  17. L20:173 excites
  18. L20:852 suppresses
  19. L21:530 suppresses
  20. L25:328 excites
  21. L27:130 suppresses
  22. L21:393 excites unclear: relative 'that' and list items
  23. L23:379 suppresses
  24. L27:358 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 -7.25 and -6.931 values between -4.03 and -3.711 values between -3.07 and -2.741 values between -2.10 and -1.785 values between -1.78 and -1.461 values between -1.46 and -1.1316 values between -1.13 and -0.8177 values between -0.81 and -0.49726 values between -0.49 and -0.171916 values between -0.17 and 0.16842 values between 0.16 and 0.48220 values between 0.48 and 0.8068 values between 0.80 and 1.1215 values between 1.12 and 1.453 values between 1.45 and 1.773 values between 1.77 and 2.094 values between 2.09 and 2.411 values between 2.41 and 2.731 values between 2.73 and 3.061 values between 3.06 and 3.382 values between 3.38 and 3.701 values between 3.70 and 4.021 values between 4.99 and 5.311 values between 5.31 and 5.63offnegativepositiveoften

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. ,F
  2. ,C
  3. ,w
  4. ,D
  5. ,s
  6. ,S
  7. ,v
  8. ,
  9. (),
  10. ,W

Suppresses

  1. ehr
  2. eft
  3. 格尔
  4. ativity
  5. QUEST
  6. 龢
  7. :'⏎
  8. hurst
  9. lica
  10. yclic