comma ending a clause before an action
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
This neuron fires on a comma that comes right after a complete phrase, when a new action is about to follow, like 'picked it up, and went' or 'you woke up, and you tried'. When it was turned up, the model's text fell into repeating filler words like 'have, have, have'.
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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unlearn” the response patterns that were prohibiting them from accepting the new cultural requirements. The consultant and top management identified the response patterns that were getting in the way, and those that were required by the organization to be able to quickly understand and embrace
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heat stopped the bleeding.⏎Curiously, the Native Americans left Thompson’s scalp next to the knocked-out Englishman. After he came to, he picked it up, and went back to Omaha
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data directory is included in the MySQL distribution:⏎MySQL Zip archive distributions for Windows contain an unmodified data directory. You can unpack such a distribution into a temporary location, then copy it⏎datadirectory to where you are setting up the new instance
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don’t just study the instrument, and look at it, and answer questions about it, and figure out how notes go. You put the instrument in your hands, and there you go — you are a practitioner.⏎“You still have to have the
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however, only works if you can brush your teeth, eat breakfast, and get ready for school. Let’s say one morning you woke up, and you tried to get dressed, but you couldn’t.⏎What if you woke
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limitations. In particular, I think it assumes that the fomite route is that the virus starts on the hands of an infected person, is transferred to an object or surface, and then picked up on the hands of
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 number of the last two and the number of the first and second, and then the number of the second and third, and the number of the third, and the first and second, and then the number of the first and third,
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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-in” methodology. It starts at the outside by identifying business outcomes, and then drills down into the feature set that will achieve those outcomes. Each feature is
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a layer or layers, highlight the ones you want to duplicate in your timeline and hit Command D.⏎You can create a pre-composition by highlighting all your layers and hitting Shift Command C. What a pre-comp will do it merge all your layers
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and collaborating with other data scientists. When you sign up, you get free access to Watson Studio and all other IBM services for 30 days. Start now and take advantage of this offer.⏎- Learn how it performs at speeds up to
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to Roman numerals. The tool basically works on a very simple concept of format conversion. In other words you just have to fill in the value of Arabic numeral and it will show the same value in Roman numeral. You can convert any desired Arabic
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
- L16:357 strongly suppresses
- L15:2643 strongly excites
- L17:2911 suppresses
- L15:1542 excites
- L17:2776 suppresses
- L15:1924 suppresses
- L16:2279 suppresses
- L16:2500 excites
- L16:1669 suppresses
- L14:1746 excites
- L15:1467 excites
- L17:173 suppresses opening bracket that adds a synonym
- L16:2247 suppresses
- L16:3014 suppresses
- L13:2929 excites
- L16:2880 suppresses
- L15:412 excites
- L14:1184 excites
- L16:2738 excites
- L16:774 suppresses
- L14:361 suppresses
- L17:585 excites
- L16:1528 excites
- L13:1066 weakly suppresses
Feeds later layers
- L19:492 strongly suppresses
- L19:1769 excites
- L26:236 excites
- L26:22 suppresses the 'res' fragment inside words
- L19:1089 excites
- L19:867 excites
- L20:1083 excites
- L27:286 excites
- L20:882 excites
- L24:216 excites
- L27:86 suppresses
- L19:845 excites
- L20:349 suppresses
- L24:199 suppresses
- L25:438 excites
- L20:1484 excites
- L20:173 excites
- L20:852 suppresses
- L21:530 suppresses
- L25:328 excites
- L27:130 suppresses
- L21:393 excites unclear: relative 'that' and list items
- L23:379 suppresses
- L27:358 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
- ,F
- ,C
- ,w
- ,D
- ,s
- ,S
- ,v
- ,
- (),
- ,W
Suppresses
- ehr
- eft
- 格尔
- ativity
- QUEST
- 龢
- :'⏎
- hurst
- lica
- yclic