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Model: GELU Model: 2 Layers, 2048 Neurons per Layer

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

Neuron 1067 in Layer 1

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-2l')



Text #0

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Max Act: 5.9036. Min Act: -0.1700

Data Index: 1520607 (Python Code)

Max Activating Token Index: 419

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Text #1

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Data Index: 1170148 (C4 (Web Text))

Max Activating Token Index: 335

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Text #2

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Max Act: 5.8411. Min Act: -0.1700

Data Index: 1419627 (Python Code)

Max Activating Token Index: 587

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Text #3

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Data Index: 738089 (C4 (Web Text))

Max Activating Token Index: 256

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Text #4

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Data Index: 743238 (C4 (Web Text))

Max Activating Token Index: 471

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Text #5

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Data Index: 1346950 (C4 (Web Text))

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Text #6

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Data Index: 456736 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 196067 (C4 (Web Text))

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Text #9

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Data Index: 790939 (C4 (Web Text))

Max Activating Token Index: 301

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Text #10

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Text #11

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Text #12

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Data Index: 964198 (C4 (Web Text))

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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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Data Index: 790292 (C4 (Web Text))

Max Activating Token Index: 213

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Text #19

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Data Index: 306966 (C4 (Web Text))

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