INDEX

Explanations

words related to specific companies, locations, and medical conditions

oai_token-act-pair · gpt-3.5-turbo

names of places, particularly those related to food and dining

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

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

orders

-0.69

glers

-0.63

ells

-0.63

ordering

-0.61

erential

-0.59

holding

-0.59

 enterprises

-0.58

aim

-0.58

actual

-0.58

 kittens

-0.56

POSITIVE LOGITS

Pacific

0.85

vironment

0.81

oola

0.80

ument

0.79

asca

0.79

 Wonderland

0.78

heim

0.74

vantage

0.74

ÃĽ

0.73

imity

0.72

Activations Density 0.355%

words related to specific companies, locations, and medical conditions

names of places, particularly those related to food and dining

No Comments

No Known Activations