zero and infinity as values
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. 11 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 responds to the number zero and to words like "infinite", especially when they name a size or limit, as in "from 0.5 to 0.9" or "would be infinite". It is quieter, and sometimes negative, on words like "negative" or "normal" in medical findings. Turning it up made the model repeat phrases, not talk about numbers.
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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five different speeds ranging from 0.5 to 0.9 mph. For the tests more than 1
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angle that a ray of sun makes with a line perpendicular to the surface. For example, a surface that directly faces the sun has a solar angle of incidence of zero, but if the surface is parallel to the sun (for example, sunrise striking
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motor is in the form of electric pulse. For each input pulse,motor shaft turns through a specified degree, called Step. The Step size may vary from 0.72° to 90°. This means that motor shaft may
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to or at the speed of light, this would cause them to gain near-infinite mass, according to the laws of relativity.⏎For example, the Official Handbook
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be visible for the character to be visible.⏎The width and height of the rectangular area are determined by the⏎value of this property.⏎For example a value of zero represents a point in the center. A⏎value of a half represents a centered
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– For healthier skin, hair and nails⏎– Helps lessen menopause symptoms⏎Silicon Dioxide 97.0%; Titanium Dioxide 0.2%; Aluminium Oxide 2.5%; Iron Oxide 0
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 "Lisbon" is a "Lisbon" with the name "Lisbon" with the name "Lisbon" as "LISBON", and the name "LISBON" is "L
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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.5⏎© 2018 Author. This work is licensed under the Creative Commons Attribution 4.0 International License.⏎Conflicts of Interest: None⏎Mild traumatic brain injury is defined as a traumatically induced physi
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On physical exam the leg has no erythema, but does have mild tenderness along the distal tibial shaft. Plain radiographs are negative. What is the most appropriate management?⏎vitamin D and calcium levels⏎MRI
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is appreciated. His temperature is 99.6°F. He has no leukocytosis and CRP and ESR are normal. Radiographs of the right leg are seen in Figure A. What is the
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for CAH. Infants who test positive need to have follow-up testing done to confirm the diagnosis. If, for some reason, the neonatal screening is negative but there is high suspicion for CAH (such as ambiguous genitalia), further
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
- L10:726 strongly suppresses
- L7:873 suppresses
- L10:1602 suppresses the number 1 as a unit value
- L8:1730 excites
- L9:977 suppresses the last digit of a decade year
- L4:622 excites
- L4:1215 excites
- L8:318 suppresses
- L4:573 excites
- L8:1305 suppresses
- L10:2828 excites
- L10:1284 excites
- L7:662 excites
- L8:1343 excites
- L9:1373 suppresses
- L10:1951 suppresses
- L7:756 weakly suppresses
- L7:213 weakly suppresses
- L9:1677 weakly suppresses
- L8:1130 weakly excites
- L9:424 weakly suppresses
- L5:449 weakly excites
- L2:2019 weakly suppresses
- L9:54 weakly excites
Feeds later layers
- L16:950 excites
- L14:2062 excites
- L12:877 excites
- L13:667 excites zeros inside decimal numbers
- L12:2435 excites
- L12:1615 excites
- L18:2221 excites
- L13:919 excites
- L13:2275 excites
- L13:2430 excites
- L16:2492 excites
- L14:1414 excites
- L14:1170 excites
- L14:478 suppresses
- L14:1176 excites
- L13:2825 excites
- L21:1228 excites
- L12:1296 excites
- L16:1710 excites
- L13:1061 excites
- L12:467 suppresses
- L22:1710 excites
- L12:44 suppresses
- L20:1768 weakly excites
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
- нич
- /null
- uting
- serv
- onCancel
- PowerPoint
- zero
- ставлен
- empty
- antly
Suppresses
- otypes
- ή
- ıkl
- 还不错
- dın
- нормальн
- bj
- exterity
- okia
- ijo