comma introducing a quoted claim
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. 21 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 comma that comes right before a full statement, especially in quotations from scripture or famous declarations, such as "We hold these truths to be self-evident, that". It is negative on some words inside longer sentences, like "so that you". Turning it up gave text that loosely echoed the trigger but mostly wandered.
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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“And, notwithstanding we believe in Christ, we keep the law of Moses, and look forward with steadfastness unto Christ, until the law shall be fulfilled.⏎“For, for this end was the law given; wherefore the law hath become dead unto
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version in the Preamble was saving too much paper. Just sayin….⏎We the People of the United States, in Order to form a more perfect Union, establish Justice, insure domestic Tranquility, provide for the common defence, promote
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He was able to bring them all into existence on day four of Creation with the word of His mouth.⏎“By the word of the Lord the heavens were made, and all the host<|endoftext|>Oxcarbazepine prevents fits.⏎Take it
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have holes and birds have nests, but the Son of Man has no place to rest."⏎American Standard Version⏎And Jesus said unto him, The foxes have holes, and the birds of the heaven have nests; but
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His, not one another's pleasure.⏎This idea found its way into our Declaration of Independence in modified form:⏎We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain
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1900); Macallum, On the Detection and Localization of Phosphorus in Animal and Vegetable Cells, Proc. Roy.⏎A curious fact, which may be used for the detection of the minutest quantity of oils and fats
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 a lot of different types of data. For example, for the entire range of the day, I may have a lot of data for the entire day, for the entire day of the day, for the entire day of the day
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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is seeking God and His direction for our lives. Praying also helps keep us out of trouble. Jesus told us to pray, "Watch and pray so that you will not fall into temptation." (Matthew 26:41)⏎Read
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you took a hypothetical "walk across Virginia," you would see changes in all of the state's ecosystems, said Roger Mann, director of research at the Virginia Institute of Marine Science in Gloucester Point. From the mountains, to the Piedmont,
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:28 "And you shall say to them, 'This is the nation that did not obey the voice of the LORD their God or accept correction; truth has perished and has been cut
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idis, a researcher in Stanford University's Kavli Institute for Particle Astrophysics and Cosmology, in collaboration with Lucio Mayer of the Swiss Federal Institute of Technology in Zurich and the University of Zurich, Chiara Mastropietro of
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
- L20:1391 excites
- L19:827 suppresses
- L18:967 suppresses
- L10:315 excites
- L10:934 suppresses
- L3:34 excites
- L18:1956 weakly excites
- L10:2370 weakly suppresses
- L12:2204 weakly suppresses
- L10:446 weakly excites
- L12:2744 weakly suppresses
- L18:1051 weakly excites
- L9:1715 weakly excites
- L17:2759 weakly suppresses
- L17:1487 weakly excites
- L16:1631 weakly suppresses
- L1:2591 weakly excites
- L5:1889 weakly excites
- L2:954 weakly excites
- L10:2448 weakly excites
- L7:966 weakly suppresses
- L7:1023 weakly suppresses
- L13:3067 weakly excites
- L5:2865 weakly excites
Feeds later layers
- L24:2911 weakly suppresses the 'cul' fragment in culprit and culminate
- L24:2105 weakly suppresses unix daemons and server services
- L23:236 weakly suppresses
- L27:1364 weakly excites
- L23:2512 weakly suppresses
- L27:899 weakly excites
- L24:2204 weakly suppresses
- L23:1643 weakly suppresses
- L22:431 weakly excites
- L24:2335 weakly excites
- L25:832 weakly suppresses zero before a decimal point
- L26:1644 weakly suppresses
- L25:223 weakly suppresses
- L25:1145 weakly suppresses
- L23:1242 weakly suppresses
- L23:71 weakly excites
- L25:427 weakly suppresses
- L23:299 weakly excites
- L23:464 weakly suppresses
- L25:1459 weakly excites
- L25:834 weakly suppresses
- L23:2722 weakly suppresses
- L26:546 weakly excites
- L24:2254 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
- &
- (&
- &
- )&
- &a
- &m
- (&(
- &C
- zym
- aming
Suppresses
- :".
- :".$
- ":"'
- 颏
- :";⏎
- +:
- TargetException
- ataires
- :<
- !: