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

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

Neuron 37 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: 7.0049. Min Act: -0.1700

Data Index: 1085259 (C4 (Web Text))

Max Activating Token Index: 323

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Text #1

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Max Act: 6.9737. Min Act: -0.1700

Data Index: 182774 (C4 (Web Text))

Max Activating Token Index: 645

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Text #2

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Max Act: 7.0674. Min Act: -0.1700

Data Index: 1042043 (C4 (Web Text))

Max Activating Token Index: 933

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Text #3

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Data Index: 742664 (C4 (Web Text))

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Text #4

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Data Index: 212626 (C4 (Web Text))

Max Activating Token Index: 645

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Text #5

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Data Index: 571225 (C4 (Web Text))

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Text #6

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Data Index: 26207 (C4 (Web Text))

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Text #7

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Data Index: 1046058 (C4 (Web Text))

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Text #8

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Data Index: 787713 (C4 (Web Text))

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Text #9

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Data Index: 782519 (C4 (Web Text))

Max Activating Token Index: 503

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Text #10

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Data Index: 585849 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 637650 (C4 (Web Text))

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Text #13

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Data Index: 1347179 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 657906 (C4 (Web Text))

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Text #16

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Data Index: 393797 (C4 (Web Text))

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Text #17

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Text #18

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Data Index: 335637 (C4 (Web Text))

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Text #19

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Data Index: 1308521 (C4 (Web Text))

Max Activating Token Index: 311

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