Neuron Explorer

Qwen3-0.6B

'that' in 'so that' purpose clauses

A neuron in layer 3 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 lights up on the word 'that' when it follows 'so' to mean 'in order that', as in 'arrange them so that they made sense'. Turning it up did not make the model write about purposes or goals; its replies just wandered.

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

    then you are done. b. If you get , then you have to algebraically manipulate your function so that you can use direct substitution: i. Factoring ii. Rationalizing (Rad

  2. #2 peak

    , model year numbers (cars), and other useful numbers there. Once they had their numbers, they needed to arrange them on the paper so that they made sense (no dividing by zero) and so that they can be solved

  3. #3 peak

    a carpenter's square.⏎Find the area of the shaded region created by the two overlapping⏎triangles in terms of a and b?⏎Position the lines so that they are perpendicular to each other.⏎What can you say about the equations of perpendicular

  4. #4 peak

    and don’t forget to limit the amount of them per day.⏎When the animals are first fed with strawberries, you should consider a small amount before leveling up so that their stomach can get used to it. Their digestive system is so sensitive that it

  5. #5 peak

    pieces, it is possible to fit the pieces together again to make a new shape. How many new shapes can you make?⏎Can you shunt the trucks so that the Cattle truck and the Sheep⏎truck change places and the Engine is back

  6. #6 peak

    . Using the rules, where⏎are they all sitting? Can you find all the possible ways?⏎What is the best way to shunt these carriages so that each train⏎can continue its journey?⏎If you split the square into these

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: because of the other (the other one, the other one, the other one, the other one, the other one, etc. etc. etc. etc. etc. etc. etc. etc. etc. etc. etc. etc

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

    or less ornamented, laid over the saddle or furniture of a horse, especially of a sumpter-horse or horse of state.⏎- Clothing, especially sumptuous clothing; equipment; outfit.⏎- To cover with a caparison,

  2. #2 peak

    me, but it never lasts longer than five minutes (32).⏎6: Correct Usage 7 | Mind you, the spare room is pretty sumptuous too; in fact, I think he gets his own Jacuzzi, so

  3. #3 peak

    have strep throat. The cause of these signs and symptoms could be a viral infection or some other illness. That's why your doctor generally tests specifically for strep throat.⏎It's also possible for you to be exposed to a person who carries

  4. #4 peak

    6: William Faulkner's Absalom, Absalom!,⏎1938: John Dos Passos's U.S.A. trilogy,⏎19<|endoftext|>A view can become a page

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. L0:2130 weakly suppresses
  2. L0:1806 weakly excites
  3. L2:829 weakly excites
  4. L0:1506 weakly excites
  5. L2:2692 weakly excites
  6. L0:1974 weakly suppresses
  7. L2:1826 weakly excites
  8. L2:2423 weakly suppresses
  9. L1:146 weakly excites
  10. L2:2817 weakly suppresses
  11. L1:2094 weakly suppresses
  12. L1:2801 weakly excites
  13. L1:1430 weakly excites
  14. L0:2825 weakly suppresses
  15. L1:2142 weakly suppresses
  16. L0:2908 weakly suppresses
  17. L0:2536 weakly excites
  18. L0:2857 weakly suppresses
  19. L2:2912 weakly excites
  20. L1:1666 weakly excites
  21. L2:493 weakly suppresses
  22. L1:2005 weakly suppresses
  23. L1:2060 weakly excites
  24. L1:638 weakly suppresses

Feeds later layers

  1. L6:1199 excites
  2. L4:653 excites "that" after "such" or "such a way"
  3. L4:2528 weakly excites
  4. L17:2834 weakly excites
  5. L8:132 weakly excites
  6. L20:2850 weakly suppresses
  7. L4:1035 weakly excites 'for' after verbs like 'fall' or 'click'
  8. L7:1673 weakly excites
  9. L23:2567 weakly suppresses
  10. L6:1395 weakly excites
  11. L4:2825 weakly excites "to" after 'for X' infinitives
  12. L4:1460 weakly excites
  13. L16:2549 weakly excites
  14. L10:2471 weakly excites
  15. L4:227 weakly excites
  16. L18:1588 weakly suppresses
  17. L27:951 weakly suppresses
  18. L6:2462 weakly excites
  19. L20:2080 weakly excites
  20. L20:2940 weakly suppresses
  21. L16:2427 weakly suppresses
  22. L17:1803 weakly suppresses
  23. L18:813 weakly excites
  24. L12:2136 weakly 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.

8 values between -0.80 and -0.5823 values between -0.58 and -0.36475 values between -0.36 and -0.142627 values between -0.14 and 0.08731 values between 0.08 and 0.3129 values between 0.31 and 0.534 values between 0.53 and 0.751 values between 0.75 and 0.971 values between 0.97 and 1.191 values between 1.19 and 1.422 values between 1.86 and 2.081 values between 2.52 and 2.751 values between 3.19 and 3.411 values between 3.63 and 3.861 values between 4.08 and 4.301 values between 4.74 and 4.961 values between 7.85 and 8.07offnegativepositiveoften

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. upply
  2. ẗ
  3. mask
  4. 的任务
  5. sidelined
  6. 产业结构
  7. あげ
  8. Cursor
  9. MASK
  10. hai

Suppresses

  1. imest
  2. elman
  3. ainer
  4. omens
  5. iaz
  6. 所在
  7. engu
  8. itos
  9. iais
  10. bour