"Please" opening a new line
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. 18 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
The neuron fires on the word "Please" when it starts a new line, often in instructions such as "Please read" or "Please cite". It goes strongly negative on "Much" starting a sentence. Turning it up gave unrelated text about maths and weather.
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 learning is based on the understanding that children develop at different rates.⏎Please find at the bottom of this page a document called 'What to expect in the
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have problems eating and getting enough fluids. Some need to have fluids given into a vein (IV) or have a feeding tube placed to get nutrition during treatment.⏎Please
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) Swarm of T-wave events during October 2005⏎Please cite this report as:⏎Global Volcanism Program, 2007
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to induce trust, every action needs both a trusted introducer and a trusted witness.⏎Please google for "gerck trust" to find newer papers, applications and also comments
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least colour differences. Polarisation, another property of EM radiation, can be detected by some organisms, with insects and cephalopods having the highest accuracy.⏎Please note, in this text, the focus has been on using EM waves to see
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⏎these crucial laws at all times. Only through constant review can we hope to⏎make guarding our tongues a habit and save ourselves from severe transgressions.⏎Please verbalize or⏎have in mind that you are studying this material as a merit
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 time that a time is more time, as time is more time with the time that is more time, as time is more time with the time that is more time, as time is more time with the more time that is more time
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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, moved by their crazed obsession with wiping away all traces of ancient civilizations, attacked it in August 2015, much the way they had previously done in Mosul, Nimrud, Hatra and Nin
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to see it to completion. Much of it was completed by University of Minnesota students. You can see all of the
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take them down. They are fortresses with layer after layer of protection, from fences to airlock-style entrances to biometric scanners.⏎Good thing, too. Much of the planet relies on these cloud fortresses, and will do so even more
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to a conductor’s ears. Not unlike a musical composition, the intricately woven notes of a successful garden involve a high level of behind-the-scene detail - much more than simply water and sun.⏎So, are you ready to become a conductor
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
- L17:2447 suppresses
- L17:1490 suppresses
- L14:2047 weakly excites
- L16:743 weakly suppresses
- L4:1344 weakly excites
- L16:2242 weakly excites
- L15:1554 weakly excites
- L15:1186 weakly excites
- L11:51 weakly suppresses
- L4:621 weakly excites
- L9:552 weakly suppresses
- L11:2124 weakly excites
- L4:1011 weakly excites
- L6:590 weakly suppresses
- L14:794 weakly suppresses
- L13:742 weakly suppresses
- L11:90 weakly suppresses
- L8:2104 weakly excites
- L17:732 weakly excites
- L5:1820 weakly suppresses
- L3:586 weakly excites
- L14:818 weakly excites
- L12:1827 weakly suppresses
- L4:1751 weakly excites
Feeds later layers
- L20:1389 weakly suppresses
- L19:1260 weakly excites
- L22:991 weakly excites
- L20:2477 weakly suppresses
- L19:463 weakly excites
- L23:1394 weakly suppresses
- L21:1790 weakly excites
- L25:998 weakly suppresses
- L19:2119 weakly excites
- L20:2876 weakly suppresses
- L23:863 weakly excites
- L20:1450 weakly excites
- L24:770 weakly suppresses
- L22:1630 weakly suppresses
- L25:1619 weakly suppresses
- L27:1004 weakly excites
- L19:599 weakly excites
- L20:3036 weakly excites
- L24:1405 weakly excites 'so' in 'so-called' and 'sores'
- L23:1584 weakly excites
- L21:939 weakly excites
- L23:543 weakly excites
- L20:1795 weakly suppresses
- L22:1377 weakly suppresses closing brackets and parentheses
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
- zie
- 起
- Convertible
- iete
- uate
- fauc
- lectic
- genesis
- 三条
- 眼角
Suppresses
- ider
- .echo
- ifndef
- Older
- ATER
- _Code
- adar
- iler
- ỗ
- uben