Neuron Explorer

Qwen3-0.6B

end of document marker

A neuron in layer 20 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 wakes up at the hidden end-of-text marker that separates one web page or document from the next. It is most active right where a document stops and an unrelated one could begin. Turning it up did not produce a clear theme in the written text.

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

    engine optimization (SEO) efforts by generating optimized content for your site. Additionally, AI can help you identify and prevent potential blog problems before they become big issues.<|endoftext|>Turbine oils are subjected to a wide range of conditions -

  2. #2 peak

    extend NumPy/SciPy and R by writing a wrapper for an Intel MKL function and then use it from NumPy/SciPy or R programs.<|endoftext|>by Roman Davidov⏎(revisited from the June 2003 issue

  3. #3 peak

    hospital for days and at the worst end your life—it’s worth it.⏎Is it mandatory to wear a helmet when snowboarding?⏎Helmets are not mandated<|endoftext|>Figurative Language Reading Comprehension Practice Cards, Green⏎- Item #:

  4. #4 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, the first train left

  5. #5 peak

    so the controllers end up talking directly to the repositories.<|endoftext|>Energy Saving Tips⏎Your Home’s Energy Use⏎Tips to Reduce Energy Consumption and

  6. #6 peak

    environmental variables, or logging properties⏎- Monitor Spark using the web UIs, metrics, and external instrumentation⏎- Understand performance tuning considerations⏎- This course is<|endoftext|>Class 1M have been learning the story of Snow White and the Seven D

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 am 246, 66, 66, 66, 66, 66, 66, 66,

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

    Help in Classification Of Relays⏎Transtutors is the best place to get answers to all your doubts regarding classification of relays with examples. Transtutors has a vast panel of experienced in classification of relays electrical engineering tutors who can explain

  2. #2 peak

    6 25.........⏎Basics: Divide integers to get integer outputs in all cases⏎Determine value using Look-up table method⏎Create Volcano (or Atoll) martix. It is an extension of Bullseye matrix problem

  3. #3 peak

    further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.⏎As the access to this document is restricted, you may want to look for

  4. #4 peak

    is now best known for the hostility to the philosophy of Plato and the strong defense of Aristotle expressed in several works, especially his Comparatio Platonis et Aristotelis / Comparison of Plato and Aristotle (1458). This book accused

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. L18:1148 strongly excites
  2. L18:1936 strongly suppresses
  3. L19:2776 strongly suppresses
  4. L15:2070 strongly excites
  5. L19:1106 excites
  6. L15:1761 suppresses
  7. L19:1479 excites
  8. L18:1512 excites end-of-document boundary token
  9. L18:1113 excites
  10. L19:1411 suppresses
  11. L18:334 suppresses
  12. L18:949 excites
  13. L17:997 excites
  14. L16:2583 excites
  15. L14:1132 suppresses
  16. L19:1527 suppresses
  17. L15:3066 suppresses
  18. L16:313 excites
  19. L18:379 suppresses
  20. L18:2222 excites
  21. L15:2391 excites
  22. L19:1105 suppresses
  23. L17:2848 excites
  24. L15:419 excites

Feeds later layers

  1. L26:156 strongly suppresses
  2. L24:303 strongly suppresses
  3. L24:96 strongly excites
  4. L26:16 strongly excites
  5. L26:288 strongly suppresses
  6. L23:194 strongly excites
  7. L27:136 strongly suppresses
  8. L25:207 strongly suppresses
  9. L26:133 strongly suppresses
  10. L27:445 strongly suppresses
  11. L21:1150 strongly suppresses
  12. L25:1274 strongly suppresses
  13. L25:144 strongly excites
  14. L26:1180 strongly suppresses
  15. L27:179 strongly excites
  16. L27:1065 strongly suppresses
  17. L22:261 strongly suppresses
  18. L27:256 strongly excites
  19. L22:221 excites period ending a contact or help sentence
  20. L24:2894 suppresses
  21. L27:309 suppresses
  22. L26:640 excites
  23. L21:217 suppresses
  24. L24:1922 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 -2.14 and -2.001 values between -1.29 and -1.153 values between -1.01 and -0.872 values between -0.87 and -0.731 values between -0.73 and -0.5917 values between -0.59 and -0.4547 values between -0.45 and -0.31184 values between -0.31 and -0.17545 values between -0.17 and -0.031065 values between -0.03 and 0.111034 values between 0.11 and 0.26632 values between 0.26 and 0.40260 values between 0.40 and 0.5494 values between 0.54 and 0.6814 values between 0.68 and 0.823 values between 0.82 and 0.962 values between 0.96 and 1.101 values between 1.24 and 1.381 values between 1.66 and 1.801 values between 3.35 and 3.49offnegativepositiveoften

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. ..."⏎
  2. ...⏎
  3. 。⏎
  4. …⏎
  5. ...⏎
  6. ."⏎
  7. ....⏎
  8. .⏎
  9. ?⏎
  10. ...'⏎

Suppresses

  1. ⏎⏎
  2. ,⏎⏎
  3. ",⏎⏎
  4. ',⏎⏎
  5. 、⏎⏎
  6. ''⏎⏎
  7. #⏎⏎
  8. (),⏎⏎
  9. ##⏎⏎
  10. !⏎⏎