blank spot before a year
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. 16 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 is active on the empty space just before a year or a number in copyright lines and dates, such as 'Copyright © 1997' or 'died January 29, 1963'. The activations are fairly weak. Turning it up or down did not produce a clear change in the writing.
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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more propositions that cannot be true simultaneously.⏎b. two or more attributes that cannot simultaneously belong to the same object.⏎Random House Unabridged Dictionary, Copyright © 1997, by Random House, Inc., on Infoplease.
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- Courier Delivery: Yes⏎- Store Delivery: Yes⏎Prices are for internet purchases only. Prices and availability in WHSmith Stores may vary significantly⏎© Copyright 2013 - 2017 WHSmith and its suppliers.⏎
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Robert Lee Frost, (born March 26, 1874, San Francisco, California, U.S.—died January 29, 1963, Boston, Massachusetts), American poet who was much admired for
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advice of his mother especially in Proverbs 31: 3 Do not spend your strength on women, your vigor on those who ruin kings
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MedicineHealth Medical Reference from Healthwise⏎To learn more visit Healthwise.org⏎© 1995-2012 Healthwise, Incorporated. Healthwise
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mus and Strabismus. I know you guys just love scientific names!⏎<|endoftext|>- George of Trebizond⏎- (1396-ca. 1472; Latin name, Trapezuntius)Humanist and
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: I have to to to to to 1 to 1 3 to 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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NGAGE. That means walk away – “We'll pick this up later, when we have a chance to cool down – it’ll be better.” You always have that choice.⏎On another level, if YOU are
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ised the 16 sixteenth notes as they go by and it is much easier than saying ‘ 1 2 3 4 5 6 7 8 9 10 11 12 1
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172.16.0.0/12 => min size for network id = 12 max size for host id = 20 10.0.0.0/8 => max size for host id
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have found disturbing concentrations of pesticides in some baby foods. And the U.S. Department of Agriculture has found weed killers widespread in finished tap water. Environmentalists have had important successes in forcing pesticides that presented unacceptably high dietary risks off the market
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
- L2:239 strongly suppresses
- L4:2532 strongly excites surname pieces split across tokens
- L0:258 strongly excites
- L2:1417 strongly suppresses
- L1:1256 strongly excites
- L2:964 strongly suppresses
- L1:831 strongly suppresses
- L4:185 strongly excites
- L1:217 strongly suppresses
- L6:1699 suppresses
- L6:394 excites
- L4:53 excites blank slot before a number
- L0:465 suppresses
- L5:1896 suppresses
- L1:95 excites
- L0:667 excites
- L2:404 excites
- L2:1607 suppresses
- L7:432 suppresses
- L6:715 excites
- L0:1916 excites
- L5:139 excites
- L4:376 suppresses
- L6:2064 excites
Feeds later layers
- L18:649 strongly suppresses
- L18:122 suppresses
- L25:422 suppresses
- L20:396 suppresses the D in 3D or 2D
- L19:581 suppresses blank slot before a number
- L18:185 excites
- L26:2003 suppresses hyphen joining two word parts
- L22:2384 suppresses
- L17:148 excites
- L22:824 suppresses blank before an expected number
- L22:372 suppresses empty spot before a number or "3D"
- L20:2800 excites
- L21:339 suppresses spot just before a year
- L18:1995 excites
- L20:344 suppresses hyphen inside compound words
- L26:1566 excites
- L27:2439 suppresses slash inside web addresses
- L27:170 suppresses unclear: spaces in mixed-language text
- L26:254 weakly excites
- L17:285 weakly suppresses
- L19:1304 weakly excites
- L27:327 weakly excites
- L19:265 weakly excites
- L24:248 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
- iance
- hom
- /output
- kind
- -kind
- i
- item
- ⏎
- ⏎⏎
- living
Suppresses
- erset
- phans
- [op
- aldi
- 是他
- .FILES
- (Size
- nog
- 蕻
- 团长