Neuron Explorer

Qwen3-0.6B

'and' joining two actions in instructions

A neuron in layer 6 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 'and' when it links two actions or objects in an explanation, such as 'take a word and insert numbers' or 'a diff takes two data sets and shows'. Its negative side is weak and touches 'by' and 'or by'. Turning it up or down did not give a clear theme in the outputs.

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

    of participants⏎- Type of participants⏎- democratic innovation yields a non-binding decision<|endoftext|>What does ‘diff’ mean in Git? A diff takes two data sets and shows you what has changed between them. Data sets can be files, commits,

  2. #2 peak

    ⏎current conversion from DC to AC, these new solar panels have a⏎solar micro inverter that takes the DC current generated by the⏎solar panel and converts it directly to AC current before leaving⏎the panel.<|endoftext|>When discussing air

  3. #3 peak

    Hash functions⏎Secure hash functions in Java⏎As you probably know if you've worked on certain algorithms such as hash tables, a hash function takes pieces of data and "randomly" maps them to integers. Generally, the resulting integers, called

  4. #4 peak

    investigator without the use of original data (but generally using the same methods).⏎reproducibility: A study is reproducible if you can take the original data and the computer code used to analyze the data and reproduce all of the numerical findings from

  5. #5 peak

    other examples of patterns you could use:⏎- Three letters, special character, three numbers⏎- Three numbers, special character, three letters⏎- Take a word and insert numbers and special characters in specific positions⏎Those are the basic components of your

  6. #6 peak

    last nationwide census in the US was undertaken in 2010, so to gauge any recent numbers, it is necessary to take the findings from that survey and project them forward to the present day. The 2010 survey revealed

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 have a good reason for the first time and the second time I am a student." I have no idea about the answer to the question. What is the best way to the question? The question is: "What is the best

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

    NCI Dictionary of Cancer Terms features 7,779 terms related to cancer and medicine.⏎Browse the dictionary by selecting a letter of the alphabet or by entering a cancer-related word or phrase in the search box.⏎- listen (A

  2. #2 peak

    so the user will have a better understanding of scatter diagrams.⏎The user can venture through the tutorial by clicking on the desired topic in one of the menus, or by using the scroll on the right side of the screen to move through the page.⏎

  3. #3 peak

    VB.NET sample project, you will learn to create a simple dictionary. The key terms are English words and each of English word is translated in to Khmer language when the word is selected

  4. #4 peak

    system, as well as the individual homeowner. You will be in the water in 30 years

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. L3:662 weakly excites
  2. L3:456 weakly suppresses
  3. L2:2809 weakly suppresses
  4. L5:216 weakly suppresses
  5. L4:726 weakly excites
  6. L2:515 weakly excites
  7. L0:2856 weakly suppresses
  8. L1:2041 weakly suppresses
  9. L5:2711 weakly excites
  10. L3:2782 weakly suppresses
  11. L1:1960 weakly excites
  12. L4:2712 weakly suppresses
  13. L0:126 weakly excites
  14. L3:2699 weakly excites
  15. L0:2983 weakly suppresses
  16. L0:776 weakly excites
  17. L3:1814 weakly suppresses
  18. L3:1966 weakly suppresses
  19. L3:528 weakly suppresses
  20. L5:2668 weakly excites closing parenthesis after a place or name
  21. L4:598 weakly excites
  22. L4:2443 weakly excites
  23. L4:165 weakly excites
  24. L1:1464 weakly excites

Feeds later layers

  1. L8:1477 excites
  2. L7:138 excites 'to' after verbs like prove or time
  3. L18:715 excites
  4. L18:529 excites
  5. L21:535 excites
  6. L9:626 excites 'and' after action verbs like click or stand
  7. L17:187 excites
  8. L19:776 excites
  9. L26:516 excites
  10. L10:3037 excites
  11. L16:2949 excites
  12. L13:1845 excites
  13. L7:1039 excites
  14. L20:2053 excites
  15. L13:887 excites
  16. L17:1592 excites
  17. L24:1251 excites
  18. L8:723 weakly excites
  19. L11:2109 weakly excites
  20. L21:239 weakly suppresses
  21. L12:2375 weakly excites
  22. L21:1076 weakly excites
  23. L9:226 weakly excites 'to' starting an infinitive
  24. L20:480 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 -1.52 and -1.361 values between -1.36 and -1.212 values between -1.06 and -0.911 values between -0.91 and -0.765 values between -0.76 and -0.6121 values between -0.61 and -0.4675 values between -0.46 and -0.31393 values between -0.31 and -0.161344 values between -0.16 and -0.001471 values between -0.00 and 0.15456 values between 0.15 and 0.3098 values between 0.30 and 0.4511 values between 0.45 and 0.606 values between 0.60 and 0.754 values between 0.75 and 0.903 values between 0.90 and 1.051 values between 1.05 and 1.202 values between 1.20 and 1.362 values between 1.36 and 1.512 values between 1.51 and 1.661 values between 1.66 and 1.811 values between 1.81 and 1.961 values between 2.11 and 2.261 values between 2.41 and 2.561 values between 2.56 and 2.722 values between 3.32 and 3.471 values between 3.77 and 3.921 values between 4.38 and 4.53offnegativepositiveoften

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. 蜱
  2. 支配
  3. erture
  4. dese
  5. 加热
  6. 运行
  7. ren
  8. 瓒
  9. read
  10. set

Suppresses

  1. 濠
  2. alent
  3. lovak
  4. ”⏎⏎
  5. idden
  6. Speedway
  7. uggested
  8. rieved
  9. lict
  10. tright