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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

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

Neuron 21 in Layer 1

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

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Max Act: 3.6646. Min Act: -0.1700

Data Index: 1233227 (C4 (Web Text))

Max Activating Token Index: 630

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Text #1

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Data Index: 1306249 (C4 (Web Text))

Max Activating Token Index: 161

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Text #2

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Max Act: 3.6333. Min Act: -0.1700

Data Index: 447238 (C4 (Web Text))

Max Activating Token Index: 534

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Text #3

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Max Act: 3.6646. Min Act: -0.1700

Data Index: 823339 (C4 (Web Text))

Max Activating Token Index: 137

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Text #4

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Max Act: 3.6333. Min Act: -0.1700

Data Index: 1087776 (C4 (Web Text))

Max Activating Token Index: 765

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Text #5

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Data Index: 762432 (C4 (Web Text))

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Text #6

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Data Index: 473961 (C4 (Web Text))

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Text #7

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Data Index: 637319 (C4 (Web Text))

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Text #8

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Max Act: 3.6020. Min Act: -0.1700

Data Index: 459479 (C4 (Web Text))

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Text #9

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Data Index: 108307 (C4 (Web Text))

Max Activating Token Index: 682

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Text #10

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Data Index: 1265508 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 229626 (C4 (Web Text))

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Text #13

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Data Index: 264092 (C4 (Web Text))

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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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Data Index: 661103 (C4 (Web Text))

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Text #19

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Data Index: 279260 (C4 (Web Text))

Max Activating Token Index: 812

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