"be" after will or you'll
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. 19 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 the word "be" when it comes straight after "will", "you'll" or "you'd", as in "you will be quizzed" or "you'll be fine". When it was turned down, the model got stuck repeating "not even", and turning it up gave text that did not follow this pattern.
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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main point; and evidence substantiation.⏎You will need to understand the sentence’s intention and keep an eye out for brevity and succinctness.⏎You will be quizzed on all the usual suspects: commas, semicolons and col
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from non-native to native English writing prowess.⏎- Like from a speaking perspective This doesn’t mean you put slang, ‘F’ words into writing. You will be provoking I don’t know who. Strictly speaking, good grammar should sound
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Skills Alphabet Activity you can possibly think of! However, it’s a rapidly growing bundle and I’ve got even more ideas coming down the pike!⏎You’ll be surprised to find great fine motor alphabet activities, games, worksheets and more! These
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if your attention to detail makes darkroom perfectionists cringe. Consistency is important, but it comes naturally with experience, and in the meantime, you’ll be just fine. I’ve made some serious mistakes in exposure, measurements, and timing
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the weight gain or loss happened over a short period of time (as is the case with crash diets and extended periods of binge eating). Generally speaking, you'll be more likely to get sick and
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their choice. You’d be amazed how coherent even a very young child’s story is. When he was
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: probably not even not even probably even not even not even not even probably even probably even probably even even not even even probably even maybe even even even even even not even even even probably even even even even even even not even even even even even
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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. So your modified file could not replace it.⏎That is why patches exist. Patches list the modifications, the line numbers and a few other useful information to be able to put that patch back into the existing code. (This process is called
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the past few weeks, thousands of native birds had felt the effects of the heat wave, both in the city and in the country.⏎“Hot weather always takes its toll, but if it only lasts for a day or two, birds can usually
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⏎Why Lesson Planet?⏎Find quality lesson planning resources, fast!⏎Share & remix collections to collaborate.⏎Organize your curriculum with collections. Easy!⏎Have time to be more creative & energetic with your students!⏎Students are introduced to the characteristics of a
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
- L18:1048 strongly suppresses
- L18:2979 strongly excites
- L17:2050 strongly excites the word 'be' after modals
- L18:776 excites
- L18:2914 suppresses
- L17:354 excites
- L16:2026 excites
- L18:1135 excites
- L14:2710 suppresses
- L18:1910 excites
- L10:586 excites 'important' and degree words after 'how'
- L18:1302 excites
- L18:2411 weakly suppresses
- L16:674 weakly excites
- L10:105 weakly suppresses
- L15:830 weakly excites
- L15:286 weakly excites
- L13:894 weakly excites 'of' after a person's name
- L15:404 weakly excites
- L16:429 weakly excites
- L17:345 weakly suppresses
- L16:968 weakly suppresses
- L8:232 weakly suppresses
- L14:282 weakly excites
Feeds later layers
- L20:1684 strongly suppresses
- L27:644 strongly suppresses
- L22:445 suppresses
- L27:655 suppresses
- L23:999 excites "be" after modal verbs
- L20:2909 suppresses
- L22:2150 suppresses
- L25:1767 suppresses
- L21:1396 suppresses
- L23:103 excites
- L21:1226 suppresses
- L22:1690 suppresses
- L24:291 suppresses
- L21:1044 suppresses
- L21:1973 suppresses
- L23:377 suppresses
- L26:1554 suppresses
- L27:1006 suppresses
- L27:1163 suppresses
- L22:1416 suppresses
- L23:667 suppresses
- L26:1007 suppresses
- L21:1360 suppresses
- L20:663 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
- 本网
- pository
- 本网站
- ród
- rror
- ashtra
- izedName
- ajor
- 年第
- able
Suppresses
- also
- also
- 也可能
- 也
- Also
- still
- 也不
- também
- 也只是
- 也都