end of document boundary token
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. 14 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 at the invisible marker that signals one web page or document has ended and another begins. It is mostly quiet on ordinary words. Turning it up made the model's writing drift into unrelated, rambling topics.
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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this video with your parents, friends, and/or adults and ask them if they can solve the problem as well⏎*Inspired by the movie Good Will Hunting<|endoftext|>Keats was one of the most life-loving people you could hope to meet,
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.⏎The source code (with examples) is here: hideinfo.cpp.⏎This software comes with no warrantee of any sort, use at your own risk!<|endoftext|>Mind Ransomware is one of those infections that are supposedly released for “educ
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1⏎By the end of Tuesday 16th please upload your piece ‘On D’ onto Moodle. Lots of dynamics and effects and different textures please!<|endoftext|>WOLFRAM SYSTEM MODELER⏎This
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00 training examples, you can choose to pick 100 random samples (batch size=100) for each EPOCH (Training cycle)<|endoftext|>|Origin:||co
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that is made terrible by our own mad attempt to interpret it as though it had⏎an underlying truth."⏎-- Umberto Eco⏎More information about the Python-list<|endoftext|>Jayne Davis: “I am not convinced in my area of research there are
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.⏎Download or subscribe to this show at https://twit.tv/shows/triangulation.⏎Thanks to Cachefly for the bandwidth for this show.<|endoftext|>The Scarlet Letter is an 1850 romantic work of fiction in a
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 concept of a highly detailed, complex, and highly advanced world in which there are no boundaries of the entire planet's spatial complexity, and the entire world of the 22000 level of human civilization has been determined to the
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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FLs). Installing one CFL saves $15 annually, according to the Rocky Mountain Institute, a nonprofit energy research group. Multiply that by the number of lamps and fixtures in your home, and watch the savings add up. Some people also prefer
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more likely.⏎Many scientists believe that the combination of a hereditary susceptibility to cancer and an environmental trigger, such as exposure to a carcinogen or being obese, puts individuals at risk of developing cancer, especially at an earlier adult age.<|endoftext|>Found
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. The wholesalers and distributors took those inflated orders at face value and, erring on the side of caution, ordered even more appliances. Those seemingly small decisions added up to big problems for General Electric.⏎Forrester’s system dynamics perspective has helped
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www.healthscout.com/template.asp?id=669525<|endoftext|>It is certain, in any case, that ignorance, allied with power, is the most ferocious enemy justice can have.⏎– James Baldwin⏎Four decades of neoliberal
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
- L13:789 suppresses
- L12:144 suppresses
- L13:2738 suppresses
- L13:1489 excites
- L7:1112 excites
- L12:2212 suppresses 'to' or 'for' opening a purpose phrase
- L12:1947 suppresses
- L10:743 excites 'therefore' or 'thus' after a subject
- L8:1958 suppresses
- L5:2546 excites
- L12:1432 weakly excites
- L12:2968 weakly excites
- L13:2816 weakly suppresses
- L10:721 weakly suppresses
- L13:237 weakly suppresses
- L13:1727 weakly excites
- L13:359 weakly suppresses
- L11:2066 weakly suppresses
- L12:2683 weakly excites
- L8:401 weakly suppresses
- L13:149 weakly excites
- L7:480 weakly suppresses
- L13:1339 weakly suppresses
- L10:248 weakly suppresses
Feeds later layers
- L15:2215 suppresses
- L16:2080 weakly excites
- L16:2728 weakly suppresses
- L16:2635 weakly excites
- L18:2900 weakly suppresses
- L23:1378 weakly suppresses
- L16:80 weakly excites
- L17:2315 weakly suppresses
- L17:2685 weakly suppresses
- L21:1785 weakly excites
- L19:1681 weakly suppresses
- L15:1046 weakly excites
- L17:2873 weakly excites
- L17:2951 weakly suppresses
- L16:2874 weakly excites
- L15:2474 weakly suppresses
- L19:2705 weakly suppresses
- L19:2896 weakly suppresses
- L16:1256 weakly excites
- L16:2197 weakly suppresses
- L22:1806 weakly suppresses "to" introducing a purpose clause
- L18:1635 weakly excites
- L25:1223 weakly suppresses
- L24:90 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
- inis
- .MiddleRight
- ise
- ru
- joined
- either
- 前后
- rus
- REPORT
- side
Suppresses
- amiento
- imiento
- ển
- edom
- Comprehensive
- aje
- 了解更多
- 对我来说
- oki
- iciente