INDEX

Explanations

proper nouns and company names

oai_token-act-pair · gpt-3.5-turbo

sections of text with high-frequency numerical or statistical references

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

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 11-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.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

oun

-0.70

 tremend

-0.69

 Atlas

-0.67

 Catal

-0.63

 Monaco

-0.61

 advisors

-0.60

 eleph

-0.60

 Scandinav

-0.57

 undermin

-0.57

 scrambling

-0.57

POSITIVE LOGITS

Mah

0.90

à¤

0.89

à¥

0.89

à¨

0.87

à©

0.86

 Kejriwal

0.85

à¦

0.84

 Punjab

0.84

hra

0.83

Indian

0.83

Activations Density 0.119%

proper nouns and company names

sections of text with high-frequency numerical or statistical references

No Comments

No Known Activations