Neuron Explorer

Qwen3-0.6B

unclear: mixed, often before a number

A neuron in layer 20 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron fires on a grab bag of spots, many of them just before a number or a short word that completes the sentence, such as 'length -1' or 'value is 1'. Its negative side fires on method calls like '.info()'. Turning it up did not produce a clear theme.

Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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

    elements of the array in reverse, we need to use a loop that will iterate from length - 1 to 0. We can use a for loop or a while loop to

  2. #2 peak

    far:⏎Originally Posted by MrFujin⏎Enter a 5-charcter string: hgout⏎String#1: tough ; ASCII code decremented by 32⏎String#2: HGUOT ; reverse order⏎mov char

  3. #3 peak

    3, 5, 8, 13, 21, 34, 55… each number is the sum ( + ) of its two previous numbers. every fold in our ruler was folded on the crease

  4. #4 peak

    sequence. It is not optional.⏎- step is the step value or difference between each number in the sequence. It is optional and by default it’s value is 1.⏎If we want to iterate an array in reverse order, we need to

  5. #5 peak

    mg/kg, 5 times daily for 5 days.⏎Best of luck---⏎Search for questions⏎Still looking for answers? Try searching for what you seek or ask your own question.⏎Posted 31 Aug 2009 •

  6. #6 peak

    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

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: [12, [2, [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

    there, I get an exception, which is life as usual for a Python programmer.⏎if not server_response['successful']:⏎etag = server_response['file_handle'].info().getheader('ETag')⏎xml_document = server_response['xml_document']

  2. #2 peak

    deciding on a treatment plan and a prognosis.⏎The following are prognostic factors for bile duct cancer.⏎Removal of the tumour with surgery @(Model.HeadingTag)>⏎Complete removal of the tumour with surgery offers the best chance for long

  3. #3 peak

    , instead of writing Users.Current.User.Name, you can just write Users.Current.Name.⏎I’ll grant you that this doesn’t seem much for the User

  4. #4 peak

    stages (they have spread into nearby lymph nodes or organs far from the bile ducts) have a less favourable prognosis.⏎Location of the tumour @(Model.HeadingTag)>⏎Tumours in the distal 3rd of the bile duct

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. L9:156 weakly suppresses
  2. L19:1537 weakly suppresses
  3. L11:769 weakly excites
  4. L7:657 weakly excites
  5. L16:1592 weakly suppresses
  6. L14:2191 weakly excites
  7. L4:2461 weakly excites
  8. L16:1642 weakly suppresses
  9. L1:2453 weakly excites
  10. L10:1588 weakly excites
  11. L19:540 weakly excites
  12. L19:1598 weakly excites comma before a qualifying clause
  13. L11:36 weakly excites
  14. L13:856 weakly suppresses
  15. L6:2257 weakly excites
  16. L19:1596 weakly suppresses
  17. L3:2379 weakly excites
  18. L7:666 weakly suppresses
  19. L2:525 weakly suppresses
  20. L2:2948 weakly suppresses
  21. L5:1295 weakly suppresses
  22. L18:701 weakly excites
  23. L13:459 weakly excites
  24. L16:2206 weakly excites

Feeds later layers

  1. L21:811 strongly suppresses
  2. L25:478 suppresses
  3. L27:772 suppresses
  4. L25:1700 suppresses
  5. L26:232 suppresses
  6. L24:2100 suppresses
  7. L27:615 suppresses
  8. L22:636 suppresses
  9. L27:730 suppresses
  10. L23:1018 suppresses
  11. L26:457 weakly suppresses
  12. L23:293 weakly suppresses
  13. L22:2609 weakly excites
  14. L22:1470 weakly suppresses
  15. L26:326 weakly excites
  16. L27:315 weakly suppresses
  17. L23:540 weakly suppresses
  18. L23:2952 weakly excites
  19. L21:2979 weakly excites
  20. L24:721 weakly excites
  21. L27:1804 weakly suppresses
  22. L22:495 weakly excites
  23. L25:2793 weakly excites
  24. L27:524 weakly 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 -2.17 and -1.981 values between -1.98 and -1.782 values between -1.38 and -1.186 values between -1.18 and -0.9820 values between -0.98 and -0.7878 values between -0.78 and -0.58267 values between -0.58 and -0.39684 values between -0.39 and -0.191231 values between -0.19 and 0.011003 values between 0.01 and 0.21447 values between 0.21 and 0.41126 values between 0.41 and 0.6129 values between 0.61 and 0.818 values between 0.81 and 1.012 values between 1.01 and 1.212 values between 1.60 and 1.801 values between 5.58 and 5.78offnegativepositiveoften

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. angling
  2. odiac
  3. rends
  4. esty
  5. ignant
  6. ://'
  7. iments
  8. chap
  9. ANDLE
  10. ตร

Suppresses

  1. ["
  2. ['
  3. ["
  4. [i
  5. [k
  6. [n
  7. [-
  8. [d
  9. ["_
  10. [