Neuron Explorer

Qwen3-0.6B

'to' after a verb of sharing or using

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 the word 'to' when it follows a verb or noun phrase that asks for an action, such as 'Share and remix collections to collaborate' or 'Sign up to view'. Turned up, the model's writing got stuck in repetitive loops.

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

    caused<|endoftext|>This preview shows pages 1–2. Sign up to view the full content.⏎This preview has intentionally blurred sections. Sign up to view the full version.View Full Document⏎Unformatted text preview: 60

  2. #2 peak

    まだ⏎J-GO EDITED BY: まだ⏎If you're going to give this activity⏎a low-rating, please post a useful⏎comment to

  3. #3 peak

    .<|endoftext|>Start a 10-Day Free Trial to Unlock the Full Review⏎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

  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

  5. #5 peak

    � of the bottle with vegetable oil, and fill the remaining part with water. Next, add 10 drops of food coloring (any color will work) to the bottle. Finally, break the Alka-Seltzer tablet into a few

  6. #6 peak

    flipped and rotated in all directions. This may help to make some furtive words more readable. Also the spacing, boldness and capital case can be switched to make the letters stand out from their context. Optionally a handy hover-cross is shown

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: A)) 1) 1) 1) 1) 1) 1) 1) 1) 1) 1) 1) 1) 1) 1) 1)

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

    , tsunami, earthquake or forest fire. Reliable and clean sources of water are on the list of top resources to find and secure.⏎Significant droughts, an increase in demand and a low

  2. #2 peak

    the attitude of a parent observing a growing child's accomplishments and successes.⏎Mudita is also traditionally regarded as the most difficult of the brahmaviharas to cultivate. To show mudita is to celebrate happiness and achievement in others even when

  3. #3 peak

    . The principal producing horizon is the Bartlesville sand, found at an average depth of 1,150 feet. To January 1, 1944, the Bartlesville sand has

  4. #4 peak

    actating cows prefer temperatures below about 20-21°C. To cope with warm weather, they use a variety of strategies to maintain normal body temperature

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. L17:1297 excites
  2. L9:20 excites
  3. L17:812 excites
  4. L16:1168 excites 'to' after verbs of change
  5. L16:771 suppresses
  6. L8:328 excites
  7. L16:1137 weakly suppresses
  8. L11:506 weakly excites
  9. L17:535 weakly excites
  10. L10:155 weakly excites
  11. L16:33 weakly excites
  12. L15:184 weakly excites
  13. L3:229 weakly excites
  14. L16:1627 weakly excites
  15. L17:36 weakly excites
  16. L14:771 weakly excites
  17. L2:371 weakly excites
  18. L13:1237 weakly excites
  19. L13:132 weakly excites "of" after a noun
  20. L11:2117 weakly excites
  21. L16:489 weakly excites
  22. L16:1949 weakly excites
  23. L11:251 weakly excites
  24. L8:127 weakly excites

Feeds later layers

  1. L20:1872 excites
  2. L20:1214 excites
  3. L20:922 excites
  4. L21:2012 excites "to" before an infinitive or noun
  5. L19:2659 excites
  6. L20:810 excites
  7. L19:386 suppresses
  8. L20:1623 excites
  9. L19:1608 excites
  10. L19:2335 excites
  11. L19:2432 excites
  12. L19:2738 excites
  13. L19:2567 excites
  14. L20:1257 excites
  15. L21:1556 excites
  16. L19:2040 excites
  17. L20:1652 excites
  18. L20:1106 excites
  19. L19:385 suppresses
  20. L19:2932 excites
  21. L22:1166 excites 'to' after words needing an infinitive
  22. L21:1773 excites 'to' starting a purpose clause
  23. L19:1523 excites
  24. L24:2854 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.

3 values between -1.72 and -1.344 values between -1.34 and -0.9548 values between -0.95 and -0.57436 values between -0.57 and -0.183142 values between -0.18 and 0.20251 values between 0.20 and 0.585 values between 0.58 and 0.972 values between 0.97 and 1.353 values between 1.35 and 1.742 values between 1.74 and 2.121 values between 2.12 and 2.501 values between 2.50 and 2.892 values between 2.89 and 3.271 values between 3.65 and 4.043 values between 4.42 and 4.811 values between 5.19 and 5.572 values between 5.57 and 5.961 values between 13.25 and 13.63offnegativepositiveoften

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. 進行
  2. 进行
  3. atures
  4. retrieve
  5. 筹集
  6. overcome
  7. 赢得
  8. 获取
  9. solve
  10. _der

Suppresses

  1. izable
  2. isable
  3. ror
  4. ucing
  5. Convertible
  6. ConfigureAwait
  7. альных
  8. 梅州
  9. UserRepository
  10. /AFP