Neuron Explorer

Qwen3-0.6B

unclear: mid-sentence function words

A neuron in layer 7 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. It is featured, so it has steering outputs.

What this neuron does

The strongest moments are scattered across unrelated sentences, often on small connecting words like 'as', 'being' or 'rapidly' in the middle of a phrase. No clear topic stands out, and the model's written output under steering does not show a clear theme either.

Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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

    with pH ranging from 4.40 to 7.45, a fish survey, including interviews

  2. #2 peak

    and quality of bottled water must be as stringent as the EPA regulations which govern tap water.⏎To suggest in any way that

  3. #3 peak

    diploma. Paying for college, however, has become a daunting task and strain for many American students and families. The cost of higher education across the country is rapidly increasing, at almost double the rate of inflation, outpacing increases in financial

  4. #4 peak

    andela sat in a conference room at CERN and watched with his arms folded as his colleagues presented the latest results on the hunt for the Higgs boson

  5. #5 peak

    our books but the layout of our collection is much more light, airy and spacious. Following on from Education, I’ve been taking

  6. #6 peak

    frey, E.Godfrey@stfc.ac.uk⏎Research date: December 2008⏎E Godfrey et al., in Metal

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: I am thinking of the number 1, and I have a lot of things. What is the value of the number 2, and I have a lot of things. Let's see, so I can have some of them. 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

    bounciness up to 1.⏎- Now select the ball, and go to the Physics tab. Also click ‘Rigid Body’ and leave the type as ‘Active’. We want this to simulate animation. Now change the bounciness

  2. #2 peak

    to problems such as heart or lung damage, or even an increased risk of another cancer later on. Doctors do everything they<|endoftext|>Variety of electromagnetic radiation with frequencies between a few and a few hundred quadrillion oscillations per second, corresponding to wave

  3. #3 peak

    but with poverty rates at record highs, programs like Social Security, Medicare, the Supplemental Nutrition Assistance Program

  4. #4 peak

    issolved output=gadm36_dissolved_nocats option=del⏎Then, add unique categories to them.⏎v.category input=gadm3

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. L5:585 excites
  2. L3:399 suppresses
  3. L5:1599 suppresses
  4. L6:323 suppresses
  5. L6:984 suppresses
  6. L6:1849 excites
  7. L5:565 suppresses
  8. L6:1753 excites
  9. L5:683 suppresses
  10. L6:1139 weakly suppresses
  11. L5:117 weakly excites
  12. L6:1348 weakly suppresses
  13. L4:24 weakly excites
  14. L6:2343 weakly suppresses
  15. L6:2539 weakly suppresses
  16. L6:16 weakly excites
  17. L6:698 weakly suppresses
  18. L6:12 weakly excites
  19. L4:302 weakly excites blank slot before a number
  20. L6:130 weakly excites
  21. L5:57 weakly suppresses
  22. L6:1971 weakly suppresses
  23. L6:936 weakly excites
  24. L3:922 weakly suppresses

Feeds later layers

  1. L11:2304 suppresses
  2. L8:170 excites
  3. L10:647 suppresses
  4. L12:1170 suppresses
  5. L8:469 suppresses
  6. L15:1210 suppresses
  7. L10:463 suppresses
  8. L8:190 suppresses
  9. L9:1370 excites
  10. L15:2383 suppresses
  11. L10:2944 excites
  12. L15:2326 suppresses
  13. L14:1693 excites
  14. L10:724 excites
  15. L10:144 excites
  16. L14:1769 suppresses
  17. L11:1533 suppresses
  18. L12:1798 excites
  19. L9:292 suppresses unclear: weak scattered tokens
  20. L12:305 suppresses
  21. L15:2137 suppresses
  22. L8:131 suppresses
  23. L14:305 suppresses
  24. L9:1563 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.

2 values between -2.75 and -2.651 values between -2.65 and -2.551 values between -2.45 and -2.341 values between -2.34 and -2.242 values between -2.03 and -1.931 values between -1.93 and -1.833 values between -1.72 and -1.621 values between -1.52 and -1.412 values between -1.41 and -1.312 values between -1.31 and -1.213 values between -1.10 and -1.001 values between -1.00 and -0.905 values between -0.90 and -0.804 values between -0.80 and -0.695 values between -0.69 and -0.595 values between -0.59 and -0.497 values between -0.49 and -0.3816 values between -0.38 and -0.2822 values between -0.28 and -0.1878 values between -0.18 and -0.07473 values between -0.07 and 0.031168 values between 0.03 and 0.131043 values between 0.13 and 0.24628 values between 0.24 and 0.34288 values between 0.34 and 0.44102 values between 0.44 and 0.5536 values between 0.55 and 0.654 values between 0.65 and 0.751 values between 0.75 and 0.862 values between 0.86 and 0.961 values between 1.27 and 1.37offnegativepositiveoften

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. 独
  2. côt
  3. 她
  4. aint
  5. 獨
  6. endcode
  7. ','#
  8. ered
  9. 之称
  10. nt

Suppresses

  1. olkien
  2. хи
  3. roys
  4. ủng
  5. 咩
  6. vik
  7. -room
  8. 一件事情
  9. ompiler
  10. AGER