zeros inside large round numbers
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. 25 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 a zero in large round numbers like 10,000 or 3,000 people, where the zero is part of the number's size. Turning it down made the model write a long string of zeros, which matches what it responds to.
Written by Claude from this neuron's activations and steering outputs. Confidence: high. 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.
-
0 years ago.⏎Food used to be obtained through hunting and gathering. The paleo diet restricts foods that became common when agriculture appeared about 10,000 years ago
-
scientific curriculum that included linguistics, arts and crafts, medicine, logic, and spirituality. People in India continue to practice two ancient systems developed over 2,000 years ago to maintain health: Ayurvedic medicine, described by the
-
ense with the stored collection of models and gave the Smithsonian Institution the opportunity to collect any models it wanted. Today, the Museum’s collection exceeds 10,000 patent
-
bitaceae family. Here are some Butternut Squash Health Benefits.⏎Squash is among the oldest known crops dating back 10,000 years to Mexico and America. The name squash, which means uncooked or
-
the Gas Giant Caligine. Before the Great Crusade, Caligine II was a bustling mining world that at its peak employed more than 3,000,000 people. This population lived in cramped conditions while reinforced
-
more than 400 varieties of biscuits and employed more than 5,000 people.⏎Huntley & Palmers employed the latest technology but their
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: 0.000000000000000000000000000000000000000000000
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
ória [online]. 2006, vol.25, n.1, pp. 44-69. ISSN 1980-4369. http://dx.doi.org/10
-
, MA: WGBH Media Library & Archives. Retrieved from http://openvault.wgbh.org/catalog/V_4E4EE3EAD24043E2BC0B972CD24B1
-
5, it would imply the exit of 166.5 million individuals from poverty. In reality, the number of poor in 2004-05 turned out to be 302 million, implying that India had
-
VECE20|⏎When requesting a correction, please mention this item's handle: RePEc:taf:jeduce:v:42:y:2011:i:2:p
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
- L22:1505 strongly excites
- L23:478 strongly excites
- L23:1295 strongly suppresses
- L23:2924 strongly suppresses
- L23:615 strongly excites
- L22:909 strongly excites
- L22:1095 strongly suppresses
- L23:2761 strongly excites
- L24:1676 strongly excites zeros in large round numbers
- L24:2703 strongly suppresses
- L23:2500 strongly suppresses
- L23:510 strongly suppresses
- L23:2222 strongly excites
- L24:2879 strongly suppresses
- L23:1243 strongly suppresses the spot right before a year's last digits
- L21:242 strongly suppresses 'very' before an adjective
- L24:2118 strongly excites
- L21:538 strongly suppresses
- L21:1228 suppresses
- L21:2233 excites
- L24:2274 excites zeros after a decimal point
- L23:997 suppresses
- L20:1479 excites
- L24:631 excites
Feeds later layers
- L26:413 strongly suppresses
- L27:153 strongly excites the spot just before a historical number
- L27:396 strongly suppresses
- L27:1153 strongly suppresses
- L27:862 strongly suppresses
- L26:137 excites
- L27:1202 suppresses
- L26:476 suppresses
- L27:1111 suppresses
- L27:1132 excites
- L26:172 suppresses
- L26:848 suppresses
- L26:793 excites
- L27:978 suppresses
- L27:448 excites
- L27:113 weakly excites
- L27:163 weakly excites
- L26:423 weakly excites
- L27:287 weakly suppresses
- L26:611 weakly suppresses
- L26:667 weakly suppresses
- L27:2172 weakly excites
- L27:992 weakly excites
- L27:132 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
- ope
- OTOR
- โต
- GetObject
- OTT
- [obj
- SCO
- ordination
- opes
- NSMutable
Suppresses
- 0
- 0
- ₀
- zero
- 零
- Zero
- -zero
- Zero
- _zero
- zeroes