document boundary end-of-text token
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. 15 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
Fires on the hidden 'end of text' marker that separates one document from the next, placed in the middle of a passage where a new, unrelated text begins. Its negative side is on pieces of file names or code tokens. Turning it up gave text with no clear link to the trigger.
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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are carried over to the new data directory.⏎Stop the existing MySQL instance using the data directory. This must be a clean shutdown<|endoftext|>On April 16, 1853, the first train left
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. Shapiro added that human hunters could have exterminated species that were already weakened by climatic and environmental changes.⏎The smell of bison DNA⏎The mitochondrial DNA<|endoftext|>Comfrey - Symphytum officinale - 5 Seeds - Medic
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,0<|endoftext|>Guidelines for Restoring Cultural Landscapes⏎Identifying, retaining and preserving
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been detected about 4 to 6 times more frequently in the high-use areas than elsewhere.⏎In addition to its studies of ambient ground water, USGS is<|endoftext|>
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code<|endoftext|>Jet engines, or gas turbines, suck in air at the front with a fan
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different aspect of the question of uniqueness is addressed in the spotlight text The many ways of building an empty, unchanging universe.⏎Synonyms: uniqueness theorems<|endoftext|>(b) A small bone that is part of the partition between the nostrils in
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 things I have been thinking about, the things that I have been thinking about, the things that I have been thinking about ... the things that I have been thinking about ... ... the ... the ... the ... the ... the ... ... the
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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output=gadm36_dissolved_nocats option=del⏎Then, add unique categories to them.⏎v.category input=gadm36_dissolved_nocats output=gadm36_dissolved_cats option=add⏎Figure
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: Extract Compressed Drupal⏎Extract the Drupal zip file in the /var/www/html directory using following command:⏎# cd /var/www/html⏎# unzip drupal-7.33.zip⏎It will create a folder as /var/www
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you can see the other students’ posts. Submit your initial post(s) early in the module.⏎See the Discussion Board Guidelines and Rubrics⏎Download Discussion Board Guidelines and Rubrics.⏎Reh, F. J. (2018
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.⏎typedef void * model_3d_ref;⏎model_3d_ref load_model_from_disk(const char * absolute_file_path);⏎void draw_model(model_3d_ref the_model, float
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
- L13:2924 strongly suppresses
- L12:689 excites
- L12:1368 excites
- L14:1294 excites
- L14:2719 suppresses
- L14:1078 excites
- L14:1379 suppresses
- L14:1471 excites
- L13:1385 suppresses
- L7:143 excites
- L14:2219 excites
- L11:2187 excites
- L14:2280 excites
- L13:2175 excites
- L13:879 excites
- L10:2259 excites
- L13:1268 excites
- L11:707 excites
- L13:2827 suppresses
- L14:2277 suppresses
- L9:1056 excites
- L14:2336 excites
- L14:2406 suppresses
- L11:647 suppresses
Feeds later layers
- L16:2777 strongly suppresses
- L17:1098 strongly suppresses
- L19:568 suppresses
- L16:1170 suppresses
- L16:2174 suppresses
- L16:1476 suppresses
- L16:1375 excites
- L16:343 suppresses
- L16:878 weakly suppresses
- L19:2456 weakly excites
- L19:1623 weakly excites
- L19:1037 weakly excites
- L18:2936 weakly excites
- L18:322 weakly suppresses
- L19:2260 weakly excites
- L19:1106 weakly excites
- L16:1362 weakly suppresses
- L22:135 weakly excites
- L17:1419 weakly excites
- L19:280 weakly excites
- L18:1917 weakly suppresses
- L17:274 weakly suppresses
- L18:2210 weakly excites
- L17:549 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
- udence
- ński
- ję
- unintention
- uş
- gomery
- .toHexString
- unos
- mers
- PLEX
Suppresses
- 斫
- 他自己
- 俎
- 所以他
- 着他
- 他是一个
- 립
- hamstring
- 他曾
- 硎