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

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

Neuron 40 in Layer 2

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: 4.2781. Min Act: -0.1700

Data Index: 186825 (C4 (Web Text))

Max Activating Token Index: 784

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Text #1

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Data Index: 193470 (C4 (Web Text))

Max Activating Token Index: 1022

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Text #2

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Max Act: 4.0280. Min Act: -0.1700

Data Index: 335194 (C4 (Web Text))

Max Activating Token Index: 691

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Text #3

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Data Index: 422330 (C4 (Web Text))

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Text #4

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Data Index: 905643 (C4 (Web Text))

Max Activating Token Index: 738

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Text #5

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Text #6

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Data Index: 405445 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 444002 (C4 (Web Text))

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Text #9

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Data Index: 860520 (C4 (Web Text))

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Text #10

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Text #11

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Text #12

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Text #13

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Text #14

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Text #15

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Text #16

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Text #17

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Text #18

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Text #19

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Data Index: 717090 (C4 (Web Text))

Max Activating Token Index: 367

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