Neuron Explorer

Qwen3-0.6B

'non' before a hyphen or adjective

A neuron in layer 25 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 prefix 'non' (and 'semi') when it starts a word meaning 'not', such as 'non-linear', 'non-Hispanic' or 'non-significant'. Turning it up or down changed the text in ways that did not clearly show this, though the word 'normal' appeared often when it was turned up.

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

    completely different outcomes.⏎In 1963, Lorenz introduced the concept of what became known as the Lorenz attractor in his seminal paper Deterministic nonperiodic flow in

  2. #2 peak

    at five locations were analysed, three of which had been affected by DFTD during this time interval. Significant increases in inbreeding coefficient (𝑓) and non-significant reductions in effective population size were observed for both diseased and non-d

  3. #3 peak

    pc) from earth and it's recessional velocity (km/s)...?⏎- Inversely proportional⏎- Directly proportional⏎- Linearly related⏎- Non-linearly related⏎Similar Physics resources:<|endoftext|>RNA functions as the central conduit for

  4. #4 peak

    1990 to 2019. The researchers analyzed life expectancy data for the 3 largest race/ethnicity groups by state: Hispanic, non-Hispanic Black, and non-Hispanic White Americans. They found that

  5. #5 peak

    through interviews and recorded into a dedicated online system. The Pearsonχ2 test, multivariate logistic regression models and discriminant models were fitted into its comparisons with the non-norovirus group and other pathogens.⏎Norovirus was detected in

  6. #6 peak

    , knowing these techniques can enable you how your current or future AI project will be built.⏎The four basic techniques of ML are: supervised , unsupervised, semi-supervised ,and reinforcement learning. There are other Machine Learning techniques, so the

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: when I am in nature, I can see much more than I can control. When I am in nature, I can control nothing, yet I can still have an active experience when I am in nature. When I am in nature, I

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

    the defeat of her forces against Octavian, the future first emperor of Rome.⏎Cleopatra, born in 69 B.C., was made Cleopatra VII, queen of Egypt, upon the death of her father, Pto

  2. #2 peak

    of readiness for cost of carbon and water resilience, and because it is “mildly supportive of low carbon regulation.” One other company, the UK’s Antofagasta, was found to show support for policies to avert climate change.

  3. #3 peak

    and power output of AMP's smart meters are well within FCC safe exposure levels. When we tested our meters, our readings were between 1 and 6 microwatts per square centimeter when 2 feet away from the meter, compared to

  4. #4 peak

    only two green auroral rings, but their reflections off the serene lake. Visible in the distant background sky is the band of our Milky Way Galaxy, the Pleiades open clusters of stars and the Andromeda galaxy.”⏎A NASA original,

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. L19:1224 suppresses
  2. L4:2006 suppresses
  3. L6:2532 excites
  4. L3:838 suppresses
  5. L20:633 suppresses
  6. L20:1626 excites
  7. L20:196 suppresses
  8. L9:2942 excites
  9. L9:1620 weakly suppresses
  10. L4:2501 weakly excites
  11. L20:238 weakly excites
  12. L10:503 weakly excites
  13. L10:656 weakly excites
  14. L17:2790 weakly suppresses
  15. L8:396 weakly suppresses
  16. L17:110 weakly suppresses
  17. L2:1127 weakly excites
  18. L14:749 weakly excites
  19. L12:1508 weakly suppresses
  20. L17:915 weakly suppresses
  21. L22:154 weakly suppresses
  22. L7:2231 weakly suppresses
  23. L10:263 weakly excites
  24. L22:102 weakly excites

Feeds later layers

  1. L26:1643 excites
  2. L27:1340 weakly excites
  3. L26:427 weakly excites
  4. L26:1496 weakly suppresses
  5. L27:1012 weakly suppresses
  6. L27:2986 weakly suppresses
  7. L27:837 weakly suppresses
  8. L26:843 weakly suppresses
  9. L27:409 weakly suppresses
  10. L27:2350 weakly suppresses
  11. L27:2199 weakly suppresses
  12. L26:2787 weakly suppresses
  13. L27:1529 weakly suppresses
  14. L26:2213 weakly excites
  15. L27:2762 weakly excites
  16. L26:470 weakly suppresses
  17. L26:1691 weakly suppresses
  18. L26:2374 weakly excites
  19. L27:3054 weakly excites
  20. L27:1320 weakly excites
  21. L26:3055 weakly excites
  22. L26:2188 weakly suppresses
  23. L27:985 weakly suppresses
  24. L27:1339 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 -21.02 and -20.211 values between -16.97 and -16.161 values between -14.54 and -13.731 values between -9.68 and -8.882 values between -8.88 and -8.073 values between -8.07 and -7.261 values between -7.26 and -6.453 values between -6.45 and -5.642 values between -5.64 and -4.832 values between -4.83 and -4.028 values between -4.02 and -3.216 values between -3.21 and -2.4020 values between -2.40 and -1.59131 values between -1.59 and -0.782386 values between -0.78 and 0.031182 values between 0.03 and 0.8484 values between 0.84 and 1.6529 values between 1.65 and 2.4613 values between 2.46 and 3.2711 values between 3.27 and 4.088 values between 4.08 and 4.883 values between 4.88 and 5.694 values between 5.69 and 6.501 values between 6.50 and 7.312 values between 7.31 and 8.121 values between 8.12 and 8.932 values between 10.55 and 11.36offnegativepositiveoften

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. PARAM
  2. Normal
  3. normal
  4. Parameter
  5. Normal
  6. parameter
  7. [param
  8. Param
  9. normally
  10. 线

Suppresses

  1. emes
  2. eme
  3. wish
  4. emd
  5. wipe
  6. traction
  7. _TAC
  8. idine
  9. emic
  10. Ả