INDEX

Explanations

proper nouns, particularly related to airlines and specific flight incidents

oai_token-act-pair · gpt-3.5-turbo Triggered by @bot

New Auto-Interp

Configuration

jbloom/Gemma-2b-IT-Residual-Stream-SAEs/gemma_2b_it_blocks.12.hook_resid_post_16384

Prompts (Dashboard)

24,576 prompts, 128 tokens each

Dataset (Dashboard)

HuggingFaceFW/fineweb

Features

16,384

Data Type

float32

Hook Name

blocks.12.hook_resid_post

Hook Layer

Architecture

standard

Context Size

1,024

Dataset

Skylion007/openwebtext

Activation Function

relu

Embeds

PlotsExplanationShow Test FieldDefault Test Text

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

 romero

-0.53

 Walkover

-0.53

 pappa

-0.53

 Knoblauch

-0.52

 FOTO

-0.50

 sentra

-0.49

 jawa

-0.48

 Octobre

-0.47

 fisk

-0.46

 Voulez

-0.46

POSITIVE LOGITS

 Middles

0.84

 McLaugh

0.79

 pegasus

0.78

 Incenti

0.70

 hentai

0.69

 homeward

0.69

 Daven

0.68

 Vaugh

0.68

 hasbro

0.66

 shenan

0.66

Activations Density 0.251%

proper nouns, particularly related to airlines and specific flight incidents

No Comments

No Known Activations