the article 'a' before a noun
A neuronOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in layerOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. 19 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featuredA neuron picked for the full treatment: steering outputs and a written explanation. About 3,000 of the 86,000 neurons are featured., so it has steering outputs.
What this neuron does
This neuron fires on the word 'a' when it comes right before a noun phrase, as in 'take a deep breath' or 'start a discussion'. Its steered outputs were mostly rambling or repetitive, so they don't show much about it.
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 activationThe number a neuron produces for a token. Large positive means it fired hard; negative means it pushed the other way. was highest. Amber marks positive activation; the outlined tokenA piece of text the model reads at once: often a word, sometimes part of a word or a punctuation mark. is the peak. Hover a token for its strength.
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.⏎Check out some valuable tips that students may use to prep for the Verbal Reasoning questions on the GRE:⏎Complete One or More Practice Exams⏎Taking a practice test is an important step in preparing for the GRE. Verbal Reasoning
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in which they have schools the past two years, and<|endoftext|>No discussions found⏎Start your discussion⏎Share your thoughts or question with experts in your field⏎Start a discussion⏎Found 2 matching solutions for this experiment⏎|Samples can be flash
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⏎Do you wonder how to subtract mixed numbers? Do you know how to handle unlike denominators or how to regroup or to borrow with mixed numbers? Take a deep breath and let us take it one step at a time. Click and begin
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those fine motor skills with little fingers. If you are looking for fun rubber band activities and games to play using a few other materials lying around your home, take a look at this list of amazing play ideas with rubber bands.⏎For such a simple
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, viruses or hacking.⏎Experts define vulnerability management as the process of identifying, classifying and handling vulnerabilities. A comprehensive vulnerability management system promotes consistent processes for dealing with a wide spectrum of cyber threats.⏎Part of a vulnerability management system may involve an index
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Easily.⏎- Mondly Languages.⏎- i<|endoftext|>As the citizens of the United States follow this wild and often bewildering presidential primary process, few stop to ask a very important question: why do we have primaries in the first place? In the
SteeringAdding a push along a neuron while the model writes, to see how its output changes. Turning it up or down.
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.
Here is something I have been thinking about lately: the other one, else else. A, else, or else. But now, as a a a, else else else, or else else else, or else else else, or else else else, or else else else, or
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
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Ridge, he advocated for peace with the European Americans⏎Date de dernière mise à jour : 05/07/2021⏎Ajouter un commentaire<|endoftext|>By DANIEL SUDDEATH⏎NEW ALBANY —⏎
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. Noreen Iftikhar from the healthline newsletter milk also contains magnesium, potassium, zinc, phosphorus, iron, selenium, and vitamins: A, E, K, B-12, and B- 6.
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same instrument are shifted in the same direction by the same amount - in unison. This is in sharp contrast to random errors where each individual measurement fluctuates independently of the others. Systematic errors, therefore, are usually most important when groups of
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net calorie burn numbers which help account for things such as your metabolism, so that you know how many calories are burned by that exercise in particular rather than just during that time period.⏎If you're walking between 3 and 4 miles per hour
Connections
Show on mapWhich neuronsOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in earlier layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.
Fed by earlier layers
- L16:2054 suppresses 'an' in definitions and descriptions
- L16:880 suppresses
- L4:137 excites
- L17:188 excites 'a' before a noun phrase
- L2:7 excites
- L18:569 excites
- L18:139 suppresses
- L11:331 suppresses
- L16:118 suppresses
- L14:392 suppresses
- L9:59 suppresses "a" meaning per (a day, a year)
- L18:1084 excites
- L17:391 suppresses
- L16:2248 excites
- L16:55 suppresses
- L4:412 excites
- L17:366 suppresses
- L4:221 suppresses
- L18:282 suppresses
- L16:97 suppresses
- L16:572 excites
- L18:546 suppresses
- L16:353 excites
- L11:2859 suppresses
Feeds later layers
- L23:703 strongly excites
- L26:2810 strongly excites 'a' before 'lot', 'little' or 'bit'
- L27:387 strongly excites 'a' right after 'played' or 'play'
- L27:2632 strongly excites
- L22:1881 excites
- L22:2889 excites
- L20:901 excites
- L26:1149 excites
- L26:829 suppresses
- L21:380 excites
- L22:2381 excites "a" before "bit" or "little"
- L23:266 suppresses
- L27:2097 suppresses
- L26:2554 excites
- L27:231 excites
- L23:2833 excites
- L21:592 excites
- L27:797 suppresses
- L26:1102 excites fibromyalgia and hour counts
- L22:83 suppresses
- L20:1273 excites
- L25:366 suppresses
- L23:2054 excites
- L26:190 suppresses
Activation histogramA chart of how often a neuron takes each activation value.
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.
Logit lensReading which output tokens a neuron pushes toward or away from, straight off its output weights, before the later layers have their say.
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 layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. instead.
Promotes
- /an
- (an
- lot
- an
- rous
- While
- erts
- While
- while
- while
Suppresses
- otherwise
- Otherwise
- agram
- nst
- intended
- 否则
- estead
- (entity
- entieth
- equivalent