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

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

Neuron 43 in Layer 1

Load this data into an Interactive Neuroscope

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



Text #0

Max Range: 4.8473. Min Range: -4.8473

Max Act: 4.8473. Min Act: -0.1700

Data Index: 1141475 (C4 (Web Text))

Max Activating Token Index: 724

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Text #1

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Max Act: 4.7848. Min Act: -0.1700

Data Index: 764210 (C4 (Web Text))

Max Activating Token Index: 740

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Text #2

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Max Act: 4.8160. Min Act: -0.1700

Data Index: 811966 (C4 (Web Text))

Max Activating Token Index: 779

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Text #3

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Max Act: 4.7848. Min Act: -0.1700

Data Index: 321416 (C4 (Web Text))

Max Activating Token Index: 815

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Text #4

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Data Index: 1124998 (C4 (Web Text))

Max Activating Token Index: 339

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Text #5

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Data Index: 730079 (C4 (Web Text))

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Text #6

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Data Index: 1010939 (C4 (Web Text))

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Text #7

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Data Index: 335687 (C4 (Web Text))

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Text #8

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Data Index: 1095624 (C4 (Web Text))

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Text #9

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Data Index: 1298641 (C4 (Web Text))

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Text #10

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Data Index: 1327997 (C4 (Web Text))

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Text #11

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Data Index: 93914 (C4 (Web Text))

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Text #12

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Data Index: 169247 (C4 (Web Text))

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Text #13

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Data Index: 1275941 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 905569 (C4 (Web Text))

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Text #16

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Text #17

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Text #18

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Data Index: 859243 (C4 (Web Text))

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Text #19

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Data Index: 99255 (C4 (Web Text))

Max Activating Token Index: 370

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