Neuron Explorer

Qwen3-0.6B

the word "be" after modals and "to"

A neuron in layer 9 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 "be" when it follows words like "must", "need to", "has been proved to" or "to". It seems to mark a spot where a verb such as "be" is about to come, and it is quieter on the passive words that come just before "be" ("seen", "shown"). Turning it up did not produce a clear theme in the output.

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

    Appropriate Services in Health Care have taken into account the role of linguistic and cultural communication barriers in regards to patient-provider transactions.⏎Websites should therefore be properly translated to meet the needs of the Hispanic population. We need to consider cultural

  2. #2 peak

    was found between dangerousness and withdrawal behavior mediated by negative affect, and between low ability and withdrawal behavior mediated by negative affect. The term used was not found to be associated with stigma. It is possible that previous stigma attached to the term, mental

  3. #3 peak

    maybe Dropbox has an idiomatic way of writing Python with lots of "isinstance()"s.⏎> In general, we believe that pattern matching has been proved to be a useful and expressive tool in various modern languages. In particular, many aspects of

  4. #4 peak

    Do the prep work in advance. Do as much prep work for a project as you can before you get the kids involved. Not everything on the page needs to be their work. It’s OK to help.⏎- Schedule several short sessions for one

  5. #5 peak

    are carried over to the new data directory.⏎Stop the existing MySQL instance using the data directory. This must be a clean shutdown<|endoftext|>On April 16, 1853,

  6. #6 peak

    2050 in a cost-effective way.⏎This study starts from the perspective that all gas consumption in Europe must, by 2050, be net zero carbon. This means that it

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 don't know how to make this work." The main idea is that we need to find a solution to this problem." I don't know how to find a solution. I don't know how to find a solution. I don

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

    way so that revolutionary businesses can do their thing.⏎This, of course, is hardly a novel view. Throughout the history of economic thought, government has long been seen as necessary but unproductive, a spender and regulator, rather than a value creator

  2. #2 peak

    heaves debris (ejecta) outward from the point of impact. Regolith development on asteroids also follows the lunar pattern. On Mars, sand has been shown to make up a significant portion of the regolith, whereas on Saturn’s moon

  3. #3 peak

    the world. Previously thought to be low in species diversity, the Antarctic is now known to have an unexpected richness of life. In addition, molecular techniques show Antarctica to be the birthplace of many species, driven by glacial cycles over millions of

  4. #4 peak

    2017 also happens to be the target date for the first unmanned mission for NASA’s new Space Launch System

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. L4:777 suppresses
  2. L6:541 suppresses
  3. L7:767 excites
  4. L5:165 suppresses
  5. L7:1222 excites
  6. L8:315 excites
  7. L5:1425 excites
  8. L3:384 suppresses
  9. L7:2403 suppresses
  10. L3:253 weakly suppresses
  11. L6:1103 weakly suppresses
  12. L6:2626 weakly suppresses
  13. L6:1579 weakly suppresses
  14. L7:2694 weakly excites
  15. L8:705 weakly excites
  16. L2:2003 weakly suppresses 'of' after abstract nouns like 'sense' or 'view'
  17. L5:770 weakly suppresses
  18. L8:403 weakly excites
  19. L6:992 weakly excites
  20. L3:1128 weakly suppresses
  21. L1:1184 weakly suppresses
  22. L7:135 weakly suppresses 'of' after 'issue' in citations
  23. L5:1186 weakly suppresses
  24. L7:1141 weakly excites

Feeds later layers

  1. L11:1046 excites
  2. L10:460 excites
  3. L15:487 excites
  4. L12:1761 excites
  5. L11:329 weakly suppresses number or citation fragment split
  6. L18:1220 weakly excites
  7. L11:1297 weakly excites
  8. L21:2837 weakly excites
  9. L12:570 weakly excites
  10. L13:920 weakly excites
  11. L15:1544 weakly excites
  12. L13:298 weakly excites
  13. L22:1935 weakly excites
  14. L17:334 weakly excites
  15. L18:764 weakly excites
  16. L10:279 weakly suppresses
  17. L15:1771 weakly excites
  18. L10:2405 weakly excites
  19. L16:1259 weakly suppresses
  20. L11:1309 weakly excites
  21. L14:502 weakly excites
  22. L17:951 weakly suppresses
  23. L15:126 weakly excites
  24. L27:174 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.

1 values between -3.61 and -3.421 values between -3.23 and -3.041 values between -3.04 and -2.852 values between -2.85 and -2.663 values between -2.66 and -2.475 values between -2.28 and -2.105 values between -2.10 and -1.915 values between -1.91 and -1.726 values between -1.72 and -1.534 values between -1.53 and -1.348 values between -1.34 and -1.1519 values between -1.15 and -0.9625 values between -0.96 and -0.7728 values between -0.77 and -0.5889 values between -0.58 and -0.39277 values between -0.39 and -0.201312 values between -0.20 and -0.011605 values between -0.01 and 0.18295 values between 0.18 and 0.3784 values between 0.37 and 0.5645 values between 0.56 and 0.7527 values between 0.75 and 0.9315 values between 0.93 and 1.1212 values between 1.12 and 1.316 values between 1.31 and 1.5010 values between 1.50 and 1.694 values between 1.69 and 1.881 values between 1.88 and 2.071 values between 2.07 and 2.261 values between 2.64 and 2.834 values between 2.83 and 3.022 values between 3.02 and 3.212 values between 3.21 and 3.402 values between 3.40 and 3.581 values between 3.77 and 3.96offnegativepositiveoften

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. обще
  2. annya
  3. YLE
  4. idden
  5. 岁以下
  6. oppable
  7. ITIZE
  8. nya
  9. gens
  10. egral

Suppresses

  1. Co
  2. ico
  3. �
  4. ios
  5. ica
  6. 智
  7. 列
  8. licht
  9. ocol
  10. .AddColumn