unclear: stray list markers and periods
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. 0 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 is weak and hard to pin down. It fires a little on list numbers like "1" in an opening bracket and more strongly goes quiet, or negative, on full stops that start a new line. Turning it up did not produce a clear story.
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.
-
land⏎(1808–1867) Hannah was born and raised in a
-
terminated:⏎(1) The battery surface temperature drops 20% lower than the peak value;⏎
-
bonded warehouse.⏎By cargo characteristics⏎(1) Raw material warehouse: The raw material warehouse is used to store the raw materials
-
⏎1. n. Any one of numerous species of marine gastropods belonging to N
-
40% lean protein, 20% fat and 40%
-
1:x in x.⏎For non-strict semantics it would be ok to store
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 the following things: the world, the sky, the moon, the stars, the planets, the planets, the sun, the earth, the moon, the stars, the planets, the moon, the stars,
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
the Brotherhood included:⏎The list is instructive because it shows how quickly the influence of the Brotherhood spread through international photographic exhibitions modelled on the annual London Salon⏎. The membership of the Linked Ring⏎soon included photographers from Austria (Hugo Hen
-
direct the report to the appropriate office for investigation.<|endoftext|>Skip to main content⏎Create interactive lessons using any digital content including wikis with our free sister product⏎. Get it on the⏎Pages and Files⏎Democratic Teaching Methods⏎Hidden Histories
-
⏎movies are the standard for entertainment. english⏎literature gains popularity across the world. The computer and internet are more accessible through knowledge of english⏎. Professional standards and manuals are first published in english⏎and then translated to other languages
-
not included as part of eBook file.<|endoftext|>is a former municipality in Akershus⏎, which lends its name to a municipality and a county in Norway⏎. The name originally belonged to a farm which was located near the current Old Aker
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
None: this is the first layer.
Feeds later layers
- L4:676 suppresses
- L2:280 suppresses
- L3:378 suppresses
- L3:2426 weakly suppresses
- L9:2764 weakly suppresses
- L14:338 weakly excites
- L22:314 weakly excites
- L11:2106 weakly excites
- L24:609 weakly suppresses
- L21:1208 weakly suppresses
- L21:253 weakly suppresses
- L14:2658 weakly excites
- L14:289 weakly suppresses
- L5:2936 weakly excites
- L25:1017 weakly excites
- L3:2278 weakly suppresses
- L24:2940 weakly suppresses
- L24:2755 weakly suppresses
- L2:814 weakly suppresses
- L6:2262 weakly suppresses
- L10:2608 weakly suppresses
- L25:39 weakly excites
- L21:441 weakly excites
- L7:756 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
- ud
- ude
- ew
- UMENT
- ush
- 卑
- umer
- mentation
- UM
- pletion
Suppresses
- rido
- ResponseBody
- 涨停
- accion
- yect
- ored
- arrêt
- erin
- ʝ
- 点点头