'and' joining two actions in instructions
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. 6 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 'and' when it links two actions or objects in an explanation, such as 'take a word and insert numbers' or 'a diff takes two data sets and shows'. Its negative side is weak and touches 'by' and 'or by'. Turning it up or down did not give a clear theme in the outputs.
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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of participants⏎- Type of participants⏎- democratic innovation yields a non-binding decision<|endoftext|>What does ‘diff’ mean in Git? A diff takes two data sets and shows you what has changed between them. Data sets can be files, commits,
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⏎current conversion from DC to AC, these new solar panels have a⏎solar micro inverter that takes the DC current generated by the⏎solar panel and converts it directly to AC current before leaving⏎the panel.<|endoftext|>When discussing air
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Hash functions⏎Secure hash functions in Java⏎As you probably know if you've worked on certain algorithms such as hash tables, a hash function takes pieces of data and "randomly" maps them to integers. Generally, the resulting integers, called
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investigator without the use of original data (but generally using the same methods).⏎reproducibility: A study is reproducible if you can take the original data and the computer code used to analyze the data and reproduce all of the numerical findings from
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other examples of patterns you could use:⏎- Three letters, special character, three numbers⏎- Three numbers, special character, three letters⏎- Take a word and insert numbers and special characters in specific positions⏎Those are the basic components of your
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last nationwide census in the US was undertaken in 2010, so to gauge any recent numbers, it is necessary to take the findings from that survey and project them forward to the present day. The 2010 survey revealed
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 a good reason for the first time and the second time I am a student." I have no idea about the answer to the question. What is the best way to the question? The question is: "What is the best
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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NCI Dictionary of Cancer Terms features 7,779 terms related to cancer and medicine.⏎Browse the dictionary by selecting a letter of the alphabet or by entering a cancer-related word or phrase in the search box.⏎- listen (A
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so the user will have a better understanding of scatter diagrams.⏎The user can venture through the tutorial by clicking on the desired topic in one of the menus, or by using the scroll on the right side of the screen to move through the page.⏎
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VB.NET sample project, you will learn to create a simple dictionary. The key terms are English words and each of English word is translated in to Khmer language when the word is selected
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system, as well as the individual homeowner. You will be in the water in 30 years
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
- L3:662 weakly excites
- L3:456 weakly suppresses
- L2:2809 weakly suppresses
- L5:216 weakly suppresses
- L4:726 weakly excites
- L2:515 weakly excites
- L0:2856 weakly suppresses
- L1:2041 weakly suppresses
- L5:2711 weakly excites
- L3:2782 weakly suppresses
- L1:1960 weakly excites
- L4:2712 weakly suppresses
- L0:126 weakly excites
- L3:2699 weakly excites
- L0:2983 weakly suppresses
- L0:776 weakly excites
- L3:1814 weakly suppresses
- L3:1966 weakly suppresses
- L3:528 weakly suppresses
- L5:2668 weakly excites closing parenthesis after a place or name
- L4:598 weakly excites
- L4:2443 weakly excites
- L4:165 weakly excites
- L1:1464 weakly excites
Feeds later layers
- L8:1477 excites
- L7:138 excites 'to' after verbs like prove or time
- L18:715 excites
- L18:529 excites
- L21:535 excites
- L9:626 excites 'and' after action verbs like click or stand
- L17:187 excites
- L19:776 excites
- L26:516 excites
- L10:3037 excites
- L16:2949 excites
- L13:1845 excites
- L7:1039 excites
- L20:2053 excites
- L13:887 excites
- L17:1592 excites
- L24:1251 excites
- L8:723 weakly excites
- L11:2109 weakly excites
- L21:239 weakly suppresses
- L12:2375 weakly excites
- L21:1076 weakly excites
- L9:226 weakly excites 'to' starting an infinitive
- L20:480 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
- 蜱
- 支配
- erture
- dese
- 加热
- 运行
- ren
- 瓒
- read
- set
Suppresses
- 濠
- alent
- lovak
- ”⏎⏎
- idden
- Speedway
- uggested
- rieved
- lict
- tright