unclear: common core and function-docs terms
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. 1 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. 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 is hard to pin down. It fires a little on words like 'Standards' in 'Common Core Standards', and it dips on programming terms such as 'parameters', 'prototype' and 'value' in function explanations. Turning it up or down did not give a clear change in the writing.
Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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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<|endoftext|>Thank you to DadsWorksheets.com for providing a VARIETY of math practice sheets! This website has been a great resource for practicing Math Common Core Standards. The Fact Family
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une Function, 2017, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5707683/#:~:text=It%20is%20a%20potent%
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formal construction and tone of a company job application.⏎This is the explanation as to why
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history, and society.⏎About the authors⏎Elaine Treharne is Roberta Bowman Denning Professor of Humanities and Professor of English (and, by courtesy, of German Studies) at Stanford University, as well as Director of Stanford's
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1: Download Drupal⏎First download the Drupal using following command:⏎# wget http://ftp.drupal.org/files/projects/drupal-7.33.zip⏎Step
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of a lego brick⏎- Number of bricks needed = volume of planet Earth / volume of a lego brick⏎We will need to use the following two formulas:⏎You can now code this algorithm using Python to
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: "I have been thinking about lately" (in Chinese) "我最近在思考着..." The user has been thinking about lately: "I have been thinking about lately" (in Chinese) "我最近在思考着..."
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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by the function and can be a type C data.⏎- Function name. This is the identifier in which you can use to call your function.⏎- Argument. Parameters that are passed to function of any type of C data.⏎You will declare your
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or above your loop function. You can always declare your function in two ways:⏎First and foremost, you will write part if a function is known as the function prototype above your loop function that consists of:⏎- Name of the function<|endoftext|>Taking time
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E_INVALID | FE_DIVBYZERO | FE_OVERFLOW | FE_UNDERFLOW) is non-zero, an exception has been raised. An application should either examine the return value or check the floating point exception flags to detect exceptions.⏎An application can also set
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footprint.⏎Advantages and disadvantages of using Sunpower solar panels⏎The use of solar energy is becoming
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
- L0:178 suppresses
- L0:1224 suppresses
- L0:1301 suppresses
- L0:821 excites
- L0:9 suppresses
- L0:2742 weakly excites
- L0:1001 weakly suppresses
- L0:2185 weakly excites
- L0:25 weakly excites
- L0:106 weakly suppresses unclear: 'if' opening a statement, 'local'
- L0:156 weakly excites
- L0:1 weakly suppresses
- L0:177 weakly excites
- L0:2346 weakly excites
- L0:1712 weakly excites
- L0:463 weakly excites
- L0:561 weakly suppresses
- L0:1477 weakly excites
- L0:1591 weakly suppresses
- L0:1073 weakly suppresses
- L0:2296 weakly excites
- L0:97 weakly excites
- L0:2076 weakly excites
- L0:603 weakly excites
Feeds later layers
- L22:1915 excites
- L2:1637 suppresses
- L15:1277 weakly suppresses
- L5:1079 weakly suppresses
- L19:461 weakly suppresses
- L20:190 weakly excites
- L17:2149 weakly excites
- L3:30 weakly suppresses
- L19:288 weakly excites
- L7:921 weakly excites
- L12:2394 weakly excites
- L3:2715 weakly excites
- L6:1308 weakly excites
- L20:72 weakly excites
- L19:403 weakly excites
- L15:699 weakly suppresses
- L14:1926 weakly excites
- L16:823 weakly suppresses
- L24:883 weakly excites
- L11:1700 weakly excites
- L9:2523 weakly excites
- L21:2723 weakly suppresses
- L13:1400 weakly suppresses "years" after a distance or time number
- L24:1366 weakly 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
- ..⏎⏎
- gne
- endas
- desn
- scn
- дум
- bucks
- $"
- иона
- insula
Suppresses
- 有限责任
- mest
- 成年人
- forgetting
- memory
- зап
- 骨干
- 特长
- 同事们
- conting