'how' starting a degree or manner clause
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. 17 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 on the word 'how' when it begins a question-like phrase about degree or manner, such as 'how quickly', 'how well' or 'how long'. When it was turned up, the model's text drifted into repeated, garbled phrases instead of saying anything clear.
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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heard the statistic that we spend 90 percent of our time indoors, or know that you should change your HVAC filter every three months for optimal performance—but just how air
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you have bile duct cancer, you may have questions about your prognosis. A prognosis is the doctor’s best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and
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penetrate your clothing’s fabric.⏎- SPF: On the other hand, SPF (Sun Protection Factor) serves as a timetable of sorts, allowing you to know about how long it will take before your skin begins to redden while using a product that
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fectionists set unrealistic standards for tasks they do. Often, the said task doesn’t even require much effort. But for them, their self-worth depends on how perfect their result is. Therefore, they tend to overwork and overstress to
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Glycemic index foods⏎This is where glycemic index comes into the scene. Glycemic index (GI) classifies foods based on how quickly they elevate blood sugar levels, taking pure glucose as the comparison point.⏎F
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take immediate action.⏎If you suspect that your computer is infected, speed is key. How quickly you respond to your computer's symptoms can make all the difference in how critically it is affected. Initially, don't worry about identifying the culprit. That
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: that the following for what is not in the project as a project as a possible future as a possible as a future as a future as a possible as possible as a possible as possible as a possible as possible as a possible as possible as a
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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asset base to satisfy its creditors, owners, and other providers of capital, or they will invest elsewhere.⏎The following is the WACC calculation formula:⏎WACC = E/V × Re + D/V × Rd × (1 - Tc)⏎
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25% should take the following relationship: 1.000×25 / 100 , or , 1.000×0.25 .⏎Giving us a result of 250, this
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(C, higher concentration less lower concentration) divided by the thickness of the membrane. At steady state, Fickian diffusion can be approximated by:⏎J = D (CWaterlooEmitter - groundwater) / membrane wall thickness⏎where D
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$\quad+\quad$ or $\quad-$<|endoftext|>Design for a Mosaic⏎Albert Joseph Moore
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
- L4:532 suppresses
- L15:1704 suppresses
- L15:280 excites
- L13:91 weakly excites
- L1:2396 weakly excites
- L15:604 weakly suppresses
- L2:126 weakly excites
- L6:1058 weakly suppresses
- L2:111 weakly suppresses
- L7:512 weakly suppresses
- L0:1192 weakly excites
- L16:282 weakly excites
- L13:416 weakly excites
- L15:850 weakly excites
- L11:265 weakly excites
- L16:222 weakly suppresses
- L4:1591 weakly excites
- L13:2402 weakly excites
- L2:1734 weakly excites
- L15:136 weakly suppresses
- L15:627 weakly excites
- L16:284 weakly excites
- L6:1892 weakly excites
- L16:1876 weakly excites
Feeds later layers
- L18:2652 excites
- L19:1535 excites
- L22:1046 excites
- L26:1849 excites
- L20:1295 excites
- L21:2777 excites
- L23:530 excites
- L19:1612 excites
- L19:2331 excites
- L21:1047 excites
- L24:2431 excites
- L21:916 excites
- L24:546 weakly excites
- L23:2619 weakly suppresses
- L20:1978 weakly excites
- L24:568 weakly excites
- L20:2712 weakly suppresses
- L23:711 weakly excites
- L18:538 weakly excites
- L21:2320 weakly excites
- L18:2395 weakly excites
- L19:2474 weakly excites
- L20:1733 weakly excites
- L26:1601 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
- rones
- getTable
- thumbs
- ismatic
- Handy
- atholic
- ategorized
- 滉
- _tables
- lename
Suppresses
- as
- uz
- div
- cáo
- 并非
- As
- uç
- cul
- covering