the 'a' after 'not' or 'just'
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. 2 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 lights up on the word 'a' when it comes right after words like 'Not', 'Just' or 'what exactly'. It goes quiet, or dips, on words like 'almost', 'only' and 'usually' that come before a word such as 'usually' or 'certainly'. Turning it up did not produce any 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 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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you would be willing to participate."⏎After a moment's hesitation, the confederate agreed and started to get up. The experimenter then said "Just a moment," and turned to the subject and repeated the same request. If the subject
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uncontrolled terrestrial conditions according to evolutionists, still cannot be synthesised even in the most sophisticated, high-tech laboratories of the 20th century. Not a single "transitional form", creatures which are supposed to show the gradual evolution of
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hour long debate. The panelists argued amongst themselves about what exactly a service or a microservice means. By the end of the debate I doubt any
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kids busy. Look around you and spot something ANYTHING that either you don’t see often or haven’t seen in awhile (not a person) and get excited while smiling and saying, “OMG you are never
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that must have surrounded the temples in ancient times. The principal feature in Egyptian social centers, and usually the only one to have survived, was the temple. Not a place for collective worship but rather a house of the gods, only the temple's
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tools to use technology are a problem.⏎All classrooms do not look like the schema above. For one thing teachers using technology often are in an active classroom. Not a lot of sitting down happens.⏎Or 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 way of a particular idea, and the way of a particular idea. So, you have been, and the way of a particular idea. So, the, and the way of a particular idea. So, the, and the way
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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actually unearthed in 2008, and while last year it was reported that they were suspected to be from a new species, the researchers have only now announced that they have found certain unique aspects to the fossil that definitively prove their
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eye. Those who take blood thinners as maintenance are more probable to experience this. These bleeds don’t cause loss of vision or pain. They will almost usually clear up in just a week or two.⏎Serious Causes of Eye Redness
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muscle pain, making it difficult to exit the water.⏎People who swim together can help or seek assistance in a crisis. Plus, swimming with a friend will almost certainly
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is the most powerful hormone in the human body, because growth, in some ways, is really helpful from insulin. If you’re trying to grow muscle and just obviously stay alive<|endoftext|>The international language of many industries is English, and English is the
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
- L0:1792 excites
- L1:604 excites
- L1:1055 excites
- L1:969 excites
- L1:2470 suppresses
- L1:602 weakly suppresses
- L1:1007 weakly excites name pieces inside a multi-part word
- L1:454 weakly excites
- L1:136 weakly suppresses
- L0:2376 weakly excites
- L1:1016 weakly suppresses
- L0:15 weakly suppresses
- L1:2556 weakly excites
- L1:171 weakly excites "but" after a negated clause
- L1:2105 weakly suppresses
- L1:1667 weakly excites
- L1:2800 weakly suppresses
- L0:1999 weakly excites
- L0:2571 weakly excites
- L0:571 weakly excites
- L1:2604 weakly excites
- L0:2126 weakly suppresses
- L0:1729 weakly suppresses
- L0:1974 weakly suppresses
Feeds later layers
- L17:2986 excites
- L15:791 weakly suppresses
- L14:1011 weakly suppresses
- L16:2625 weakly suppresses
- L13:2041 weakly suppresses
- L25:643 weakly suppresses
- L6:1122 weakly excites
- L22:2006 weakly suppresses
- L4:1645 weakly excites
- L23:347 weakly suppresses
- L12:1536 weakly excites
- L15:2713 weakly suppresses
- L19:2585 weakly suppresses
- L27:2859 weakly suppresses
- L27:324 weakly suppresses
- L17:2928 weakly suppresses
- L7:979 weakly suppresses middles of split scientific compound words
- L10:654 weakly excites
- L16:1671 weakly excites
- L4:2895 weakly excites 'all' in 'at all' phrases
- L16:1972 weakly suppresses
- L16:538 weakly excites
- L6:2758 weakly excites
- L14:2502 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
- likely
- explicitly
- directly
- other
- quicker
- 直接
- sooner
- store
- other
- intended
Suppresses
- itivity
- 叼
- 鲜血
- imity
- 或多
- 翡
- inges
- 这种事情
- apas
- tractive