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

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

Neuron 49 in Layer 2

Load this data into an Interactive Neuroscope

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



Text #0

Max Range: 3.3068. Min Range: -3.3068

Max Act: 3.3068. Min Act: -0.1700

Data Index: 781501 (C4 (Web Text))

Max Activating Token Index: 1003

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Text #1

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Data Index: 849948 (C4 (Web Text))

Max Activating Token Index: 853

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Text #2

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Max Act: 3.2754. Min Act: -0.1700

Data Index: 1252684 (C4 (Web Text))

Max Activating Token Index: 728

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Text #3

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Max Act: 3.2754. Min Act: -0.1700

Data Index: 252994 (C4 (Web Text))

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Text #4

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Max Act: 3.2439. Min Act: -0.1700

Data Index: 430406 (C4 (Web Text))

Max Activating Token Index: 564

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Text #5

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Data Index: 169718 (C4 (Web Text))

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Text #6

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Data Index: 757420 (C4 (Web Text))

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Text #7

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Data Index: 462875 (C4 (Web Text))

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Text #8

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Data Index: 515040 (C4 (Web Text))

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Text #9

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Data Index: 391116 (C4 (Web Text))

Max Activating Token Index: 583

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Text #10

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Data Index: 1042273 (C4 (Web Text))

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Text #11

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Data Index: 403795 (C4 (Web Text))

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Text #12

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Data Index: 1034746 (C4 (Web Text))

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Text #13

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Data Index: 201533 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 959110 (C4 (Web Text))

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Text #16

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Data Index: 530810 (C4 (Web Text))

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Text #17

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Data Index: 439460 (C4 (Web Text))

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Text #18

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Data Index: 363268 (C4 (Web Text))

Max Activating Token Index: 758

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Text #19

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Data Index: 587260 (C4 (Web Text))

Max Activating Token Index: 330

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