INDEX

Explanations

proper nouns related to specific locations or organizations

oai_token-act-pair · gpt-3.5-turbo

mentions of specific locations and institutions, particularly in Baton Rouge

oai_token-act-pair · gpt-4o-mini Triggered by @bot

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 9-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.hook_resid_pre

Prompts (Dashboard)

24,576 prompts, 128 tokens each

Dataset (Dashboard)

Skylion007/openwebtext

Features

24,576

Data Type

torch.float32

Hook Point

blocks.9.hook_resid_pre

Architecture

standard

Context Size

128

Dataset

Skylion007/openwebtext

Hook Point Layer

Activation Function

relu

Embeds

PlotsExplanationShow Test FieldDefault Test Text

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

aternity

-0.85

sle

-0.77

ãĥĥãĥĪ

-0.76

spring

-0.75

reads

-0.73

lessness

-0.73

ality

-0.73

isd

-0.70

frames

-0.70

ulner

-0.70

POSITIVE LOGITS

DAQ

0.91

TY

0.87

ystem

0.83

cape

0.83

TING

0.81

yard

0.81

iants

0.80

 Rouge

0.74

hip

0.72

 Yards

0.72

Activations Density 0.128%

proper nouns related to specific locations or organizations

mentions of specific locations and institutions, particularly in Baton Rouge

No Comments

No Known Activations