Neuron Explorer

Qwen3-0.6B

"be" after will or you'll

A neuron in layer 19 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 "be" when it comes straight after "will", "you'll" or "you'd", as in "you will be quizzed" or "you'll be fine". When it was turned down, the model got stuck repeating "not even", and turning it up gave text that did not follow this pattern.

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

    main point; and evidence substantiation.⏎You will need to understand the sentence’s intention and keep an eye out for brevity and succinctness.⏎You will be quizzed on all the usual suspects: commas, semicolons and col

  2. #2 peak

    from non-native to native English writing prowess.⏎- Like from a speaking perspective This doesn’t mean you put slang, ‘F’ words into writing. You will be provoking I don’t know who. Strictly speaking, good grammar should sound

  3. #3 peak

    Skills Alphabet Activity you can possibly think of! However, it’s a rapidly growing bundle and I’ve got even more ideas coming down the pike!⏎You’ll be surprised to find great fine motor alphabet activities, games, worksheets and more! These

  4. #4 peak

    if your attention to detail makes darkroom perfectionists cringe. Consistency is important, but it comes naturally with experience, and in the meantime, you’ll be just fine. I’ve made some serious mistakes in exposure, measurements, and timing

  5. #5 peak

    the weight gain or loss happened over a short period of time (as is the case with crash diets and extended periods of binge eating). Generally speaking, you'll be more likely to get sick and

  6. #6 peak

    their choice. You’d be amazed how coherent even a very young child’s story is. When he was

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: probably not even not even probably even not even not even not even probably even probably even probably even even not even even probably even maybe even even even even even not even even even probably even even even even even even not even even even even even

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

    Why Lesson Planet?⏎Find quality lesson planning resources, fast!⏎Share & remix collections to collaborate.⏎Organize your curriculum with collections. Easy!⏎Have time to be more creative & energetic with your students!⏎Students participate in a variety of physical activities

  2. #2 peak

    . So your modified file could not replace it.⏎That is why patches exist. Patches list the modifications, the line numbers and a few other useful information to be able to put that patch back into the existing code. (This process is called

  3. #3 peak

    the past few weeks, thousands of native birds had felt the effects of the heat wave, both in the city and in the country.⏎“Hot weather always takes its toll, but if it only lasts for a day or two, birds can usually

  4. #4 peak

    ⏎Why Lesson Planet?⏎Find quality lesson planning resources, fast!⏎Share & remix collections to collaborate.⏎Organize your curriculum with collections. Easy!⏎Have time to be more creative & energetic with your students!⏎Students are introduced to the characteristics of a

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. L18:1048 strongly suppresses
  2. L18:2979 strongly excites
  3. L17:2050 strongly excites the word 'be' after modals
  4. L18:776 excites
  5. L18:2914 suppresses
  6. L17:354 excites
  7. L16:2026 excites
  8. L18:1135 excites
  9. L14:2710 suppresses
  10. L18:1910 excites
  11. L10:586 excites 'important' and degree words after 'how'
  12. L18:1302 excites
  13. L18:2411 weakly suppresses
  14. L16:674 weakly excites
  15. L10:105 weakly suppresses
  16. L15:830 weakly excites
  17. L15:286 weakly excites
  18. L13:894 weakly excites 'of' after a person's name
  19. L15:404 weakly excites
  20. L16:429 weakly excites
  21. L17:345 weakly suppresses
  22. L16:968 weakly suppresses
  23. L8:232 weakly suppresses
  24. L14:282 weakly excites

Feeds later layers

  1. L20:1684 strongly suppresses
  2. L27:644 strongly suppresses
  3. L22:445 suppresses
  4. L27:655 suppresses
  5. L23:999 excites "be" after modal verbs
  6. L20:2909 suppresses
  7. L22:2150 suppresses
  8. L25:1767 suppresses
  9. L21:1396 suppresses
  10. L23:103 excites
  11. L21:1226 suppresses
  12. L22:1690 suppresses
  13. L24:291 suppresses
  14. L21:1044 suppresses
  15. L21:1973 suppresses
  16. L23:377 suppresses
  17. L26:1554 suppresses
  18. L27:1006 suppresses
  19. L27:1163 suppresses
  20. L22:1416 suppresses
  21. L23:667 suppresses
  22. L26:1007 suppresses
  23. L21:1360 suppresses
  24. L20:663 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.

3 values between -6.20 and -5.412 values between -5.41 and -4.628 values between -4.62 and -3.8216 values between -3.82 and -3.0344 values between -3.03 and -2.24130 values between -2.24 and -1.45377 values between -1.45 and -0.662118 values between -0.66 and 0.13633 values between 0.13 and 0.93205 values between 0.93 and 1.72116 values between 1.72 and 2.5177 values between 2.51 and 3.3041 values between 3.30 and 4.0928 values between 4.09 and 4.8928 values between 4.89 and 5.6818 values between 5.68 and 6.4710 values between 6.47 and 7.2610 values between 7.26 and 8.0512 values between 8.05 and 8.844 values between 8.84 and 9.649 values between 9.64 and 10.434 values between 11.22 and 12.012 values between 12.01 and 12.803 values between 12.80 and 13.591 values between 14.39 and 15.182 values between 15.18 and 15.974 values between 15.97 and 16.761 values between 17.55 and 18.341 values between 19.93 and 20.721 values between 24.68 and 25.47offnegativepositiveoften

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. 本网
  2. pository
  3. 本网站
  4. ród
  5. rror
  6. ashtra
  7. izedName
  8. ajor
  9. 年第
  10. able

Suppresses

  1. also
  2. also
  3. 也可能
  4. 也
  5. Also
  6. still
  7. 也不
  8. também
  9. 也只是
  10. 也都