indefinite 'a' after a verb
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. 17 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them 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 small word 'a' or 'an' right after a verb, as in 'earn a commission', 'get a custom', or 'need a space'. It is the word just before a new noun phrase begins. Turning it up did not make the writing noticeably about this, so the link to the output is weak.
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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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: a 2.3.2.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
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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
- L16:1672 excites
- L9:1571 excites
- L16:1876 suppresses
- L5:2748 excites
- L14:2868 excites
- L10:354 excites
- L13:2136 suppresses
- L6:2635 weakly excites
- L10:2169 weakly suppresses
- L16:2486 weakly suppresses
- L14:2637 weakly excites
- L15:1386 weakly excites prepositions after passive verbs
- L15:2583 weakly excites
- L9:820 weakly excites
- L5:519 weakly excites
- L16:2270 weakly suppresses
- L16:2855 weakly excites
- L16:1777 weakly excites
- L15:1408 weakly excites
- L9:1239 weakly excites
- L13:885 weakly suppresses
- L4:1202 weakly excites
- L15:1507 weakly excites
- L15:2873 weakly excites
Feeds later layers
- L19:1501 suppresses
- L18:934 suppresses
- L19:776 excites
- L18:1278 suppresses 'a' or 'most' before a quantity
- L18:2301 suppresses
- L18:141 weakly suppresses
- L20:1103 weakly suppresses
- L19:832 weakly suppresses
- L20:851 weakly suppresses
- L18:780 weakly excites
- L20:2692 weakly excites
- L18:2534 weakly suppresses
- L21:247 weakly excites colon after a said or explains verb
- L21:1971 weakly excites
- L19:106 weakly suppresses
- L18:1235 weakly excites
- L21:540 weakly excites
- L19:778 weakly suppresses
- L25:339 weakly suppresses
- L25:3045 weakly excites
- L20:1554 weakly suppresses
- L18:487 weakly excites
- L27:587 weakly suppresses
- L19:2418 weakly 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
- avity
- 衔
- bidden
- ursal
- DownLatch
- orno
- mine
- DCALL
- race
- prise
Suppresses
- 合适的
- suitable
- 合适
- uitable
- appropriate
- corresponding
- 适当的
- øy
- 真实的
- orthy