'to' after 'prior' (before)
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. 4 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 'to' in the phrase 'prior to', as in 'prior to 1970'. It was almost silent on most other text. When it was turned up, the written text did not clearly change in any consistent way.
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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opportunity for you to learn more about new cultures, and explore some of the diversity that makes the world such a wonderful place.⏎Global Diversity Awareness Month timeline⏎Prior to and throughout the 2014 Olympic Games in So
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are pondering how to make your computer virus, you’ve come towards the right place. There are many tutorials and steps on making a malware. However , prior to this, it is important to understand what the pathogen is, just how it
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helps cut down on friction, making it useful for keeping skin dry and helping to prevent rashes.”⏎What’s the problem with baby powder with talc?⏎Prior to 1970, many powders contained talc which also contained asbestos
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the researchers noted that prior to the existence of carpool lanes commuters said carpooling was too expensive. After
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on CO<|endoftext|>Multilateral Trade Negotiations: Tips and Techniques (2013)⏎Duration of event:⏎Event focal point email:⏎Other events details:⏎Prior to the Uruguay Round of mult
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96, the National⏎Science Education Standards (NSES) have been⏎at the center of the science education reform⏎movement in the United States. Prior to that⏎time, the National Science Foundation, other⏎government agencies, and private
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: What is the value of `x`? So, $ x$? Let me write an equation for $ x$. Let me write $ x$ in terms of $ x$. So, $ x$? So, $ x
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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imates: Sow in late fall through winter for cool–season harvest.⏎When to Start Inside: Not recommended; transplant stress can cause plants to bolt (prematurely flower).⏎Days to Emerge: 5–10 days⏎
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recognize that as long as it is accomplished and done on time, that it is okay. In the beginning, be prepared to patiently ask and answer a lot of questions! Why do emergency numbers need to be
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cameras in hand and away from the fenced perimeter, be prepared to possibly be stopped and answer their questions regarding your visit. The staff housing located not
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’re working on⏎- Create a pre-comp to easily duplicate certain animations for re-use⏎Here’s another great example video done by Nick in After Effects using precomps!⏎Check back next week to learn the difference between frame rate and shutter speed
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
- L3:2829 excites
- L3:691 weakly excites
- L3:187 weakly excites
- L3:59 weakly excites
- L3:50 weakly excites
- L2:2648 weakly suppresses
- L3:272 weakly excites
- L3:3030 weakly excites
- L3:512 weakly suppresses
- L2:1494 weakly suppresses
- L3:456 weakly suppresses
- L1:709 weakly suppresses
- L3:122 weakly excites
- L2:41 weakly suppresses
- L2:1292 weakly suppresses
- L1:2261 weakly suppresses
- L2:1277 weakly suppresses
- L1:2076 weakly excites
- L3:464 weakly excites
- L1:2922 weakly excites
- L0:1212 weakly suppresses
- L2:493 weakly suppresses
- L2:729 weakly suppresses
- L2:1690 weakly suppresses
Feeds later layers
- L9:2535 excites
- L8:1999 excites
- L13:2439 excites
- L20:2371 excites
- L15:2342 excites
- L7:2428 excites
- L19:1298 excites
- L26:1614 weakly suppresses
- L7:1692 weakly excites
- L18:562 weakly excites
- L18:2984 weakly excites
- L8:1477 weakly excites
- L12:2991 weakly excites
- L15:2163 weakly excites
- L13:1327 weakly excites
- L9:2910 weakly suppresses
- L9:619 weakly excites
- L9:3002 weakly suppresses
- L6:794 weakly excites
- L20:1546 weakly excites
- L11:2584 weakly excites
- L8:1916 weakly excites
- L18:1933 weakly excites
- L9:563 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
- componentWill
- 准备好
- -facing
- -before
- bevor
- iores
- (grammarAccess
- before
- *</
- theless
Suppresses
- 密度
- 不理
- cern
- Vaults
- iceberg
- density
- 陸
- IMPLIED
- IMPLIED
- 各县