INDEX

Explanations

words related to physical locations, specifically bodies of water and man-made structures such as classrooms, warehouses, and stores

oai_token-act-pair · gpt-3.5-turbo

locations and places where activities or conditions occur

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

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 6-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre

Architecture

standard

Context Size

128

Dataset

Skylion007/openwebtext

Hook Point Layer

Activation Function

relu

Embeds

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

BUG

-0.63

ANC

-0.61

 Thing

-0.60

 unification

-0.57

 hypothesis

-0.57

 Encyclopedia

-0.57

IENT

-0.56

 dich

-0.56

urse

-0.55

 Heist

-0.55

POSITIVE LOGITS

hops

1.27

hips

1.23

chool

1.22

paces

1.15

pring

1.07

afety

1.03

pace

1.03

creen

1.02

hip

0.98

mith

0.97

Activations Density 0.306%

words related to physical locations, specifically bodies of water and man-made structures such as classrooms, warehouses, and stores

locations and places where activities or conditions occur

No Comments

No Known Activations