Neuron Explorer

Qwen3-0.6B

'a' right after 'being'

A neuron in layer 5 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 small word 'a' when it comes straight after 'being', as in 'Being a student'. It also fires a little on 'form' in 'formulating'. It dips on 'be' in 'happen to be' and on 'as' in 'the same as'. Turning it up did not produce any clear related theme in the 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

    of the parabola. The procedure requires only local information of the artificial neuron to which it is applied. The -th approximation step is given by:⏎Being the neuron weight of its input and is the loss function.⏎The Quickprop algorithm is

  2. #2 peak

    Other editions. Enlarge cover. Error rating book.⏎Browse more videos⏎Human Anatomy and Physiology are two most-related subjects in the field of medical sciences. Being a student, one thing you are definitely going to need is a good textbook on the

  3. #3 peak

    . Since every profession requires you to make good decisions, being a critical thinker, you can handle situations firmly. For example, a doctor without critical

  4. #4 peak

    ” and the theory of “satisficing.” He applied psychology to statistics, operations, and decision-making scenarios to help define the process that people go through when formulating solutions to problems.⏎Herbert Simon was born in Milwaukee, Wisconsin, on

  5. #5 peak

    that could impact waste isolation.⏎During her review of the report<|endoftext|>The Heilwood Company store was a product of necessity. Being a rural, isolated area, the newly created town needed a central place to purchase the

  6. #6 peak

    it has enabled us to be a better organization as we try draw attention to the needs of our communities.⏎Here are

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: the number of the book "The Art of the Computer Science" (A.T.C.) for the course of the student's knowledge, and the fact that the students are taking their first year of CS courses. It seems that the student is

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

    to seekers of knowledge.<|endoftext|>When you here the term Skinhead you probably think about young rebels⏎wearing big black boots and Nazi symbols. These happen to be a few trademarks⏎but across the world "Skinhead" refers to

  2. #2 peak

    torque readings can be directly compared to the readings taken on some other day, or even taken at some other altitude.⏎That is, the corrected readings are the same as the result that you would get by taking the car (or engine) to a

  3. #3 peak

    communicate information on these hazards. The information contained in the SDS is largely the same as the MSDS, except now the SDSs are required to be presented in a

  4. #4 peak

    most ancient attraction.⏎A unique treasure, situated in beautiful Victoria Park in the west of the city, the fossil trees uncovered by removal of the surrounding rocks are the remains of an ancient forest, around than 330 million years old.

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. L4:24 excites
  2. L4:20 suppresses
  3. L4:2209 weakly suppresses
  4. L4:1274 weakly excites word right before a term's name
  5. L2:2195 weakly suppresses
  6. L4:161 weakly suppresses
  7. L3:470 weakly suppresses
  8. L3:3013 weakly excites
  9. L4:805 weakly suppresses
  10. L4:2699 weakly excites
  11. L4:120 weakly suppresses
  12. L4:2128 weakly suppresses
  13. L3:2881 weakly excites
  14. L4:701 weakly suppresses
  15. L4:2196 weakly excites
  16. L2:379 weakly excites "the" right after "without"
  17. L0:1073 weakly excites
  18. L4:998 weakly suppresses
  19. L2:2405 weakly suppresses
  20. L3:659 weakly excites
  21. L2:1809 weakly excites
  22. L2:277 weakly excites
  23. L1:2118 weakly excites
  24. L3:2960 weakly excites

Feeds later layers

  1. L6:2082 suppresses
  2. L14:2079 weakly suppresses prepositions after comparison words
  3. L6:773 weakly suppresses
  4. L7:1981 weakly suppresses
  5. L18:2573 weakly excites
  6. L8:469 weakly suppresses
  7. L9:2096 weakly suppresses 'the' or 'as' before a superlative role
  8. L13:2430 weakly suppresses
  9. L12:2459 weakly excites
  10. L12:1692 weakly suppresses
  11. L9:1939 weakly excites
  12. L12:1531 weakly excites
  13. L7:1919 weakly suppresses
  14. L8:2347 weakly excites
  15. L11:1988 weakly excites
  16. L23:406 weakly suppresses
  17. L16:511 weakly suppresses
  18. L19:1354 weakly excites
  19. L17:2747 weakly excites
  20. L7:1016 weakly suppresses 'something' after is or not
  21. L10:999 weakly suppresses
  22. L8:2775 weakly excites
  23. L15:1292 weakly suppresses
  24. L16:731 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 -2.11 and -2.021 values between -0.88 and -0.793 values between -0.79 and -0.713 values between -0.71 and -0.625 values between -0.62 and -0.538 values between -0.53 and -0.4428 values between -0.44 and -0.35108 values between -0.35 and -0.27291 values between -0.27 and -0.18687 values between -0.18 and -0.091241 values between -0.09 and -0.001019 values between -0.00 and 0.08315 values between 0.08 and 0.17111 values between 0.17 and 0.2629 values between 0.26 and 0.3524 values between 0.35 and 0.4411 values between 0.44 and 0.527 values between 0.52 and 0.615 values between 0.61 and 0.705 values between 0.70 and 0.791 values between 0.79 and 0.872 values between 0.87 and 0.961 values between 0.96 and 1.051 values between 1.05 and 1.141 values between 1.31 and 1.40offnegativepositiveoften

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. 度
  2. inst
  3. 斯基
  4. UIL
  5. grinder
  6. getic
  7. lets
  8. uil
  9. lic
  10. fulness

Suppresses

  1. :"+
  2. :")⏎
  3. erald
  4. cased
  5. SECOND
  6. UMAN
  7. ($__
  8. :")
  9. Moo
  10. COR