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Model: GELU Model: 4 Layers, 2048 Neurons per Layer

Dataset: 80% C4 (Web Text) and 20% Python Code

Neuron 1336 in Layer 3

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-4l')



Text #0

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Max Act: 6.5974. Min Act: -0.1699

Data Index: 697874 (C4 (Web Text))

Max Activating Token Index: 203

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Text #1

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Max Act: 6.5037. Min Act: -0.1700

Data Index: 325236 (C4 (Web Text))

Max Activating Token Index: 921

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Text #2

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Max Act: 6.4412. Min Act: -0.1700

Data Index: 358387 (C4 (Web Text))

Max Activating Token Index: 1017

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Text #3

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Max Act: 6.2224. Min Act: -0.1700

Data Index: 701152 (C4 (Web Text))

Max Activating Token Index: 859

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Text #4

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Data Index: 1253504 (C4 (Web Text))

Max Activating Token Index: 433

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Text #5

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Data Index: 474897 (C4 (Web Text))

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Text #6

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Data Index: 1199198 (C4 (Web Text))

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Text #7

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Data Index: 729814 (C4 (Web Text))

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Text #8

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Data Index: 226631 (C4 (Web Text))

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Text #9

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Data Index: 44488 (C4 (Web Text))

Max Activating Token Index: 492

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Text #10

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Data Index: 804607 (C4 (Web Text))

Max Activating Token Index: 876

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Text #11

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Data Index: 1643438 (Python Code)

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Text #12

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Data Index: 916006 (C4 (Web Text))

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Text #13

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Data Index: 1019225 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 69385 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 765381 (C4 (Web Text))

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Text #18

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Data Index: 1195696 (C4 (Web Text))

Max Activating Token Index: 154

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Text #19

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Data Index: 948311 (C4 (Web Text))

Max Activating Token Index: 369

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