INDEX

Explanations

aspects related to data processing performance in large datasets

oai_token-act-pair · gpt-4o-mini

Triggered by @bot

New Auto-Interp

Top Features by Cosine Similarity

Comparing With LLAMA3.1-8B @ 9-llamascope-res-32k

Configuration

fnlp/Llama3_1-8B-Base-LXR-8x/Llama3_1-8B-Base-L9R-8x

Prompts (Dashboard)

24,576 prompts, 128 tokens each

Dataset (Dashboard)

cerebras/SlimPajama-627B

Features

32,768

Data Type

bfloat16

Hook Name

blocks.9.hook_resid_post

Hook Layer

Architecture

jumprelu

Context Size

1,024

Dataset

cerebras/SlimPajama-627B

Activation Function

relu

Embeds

IFrame

Link

Negative Logits

alat

-0.15

Directed

-0.14

nerRadius

-0.14

à¸Ńà¸£

-0.14

ras

-0.13

 Sutton

-0.13

arp

-0.13

 Consort

-0.13

 Anth

-0.13

_SR

-0.13

POSITIVE LOGITS

agos

0.17

vÃ¡l

0.15

igli

0.15

iglia

0.15

giene

0.15

Ã¸re

0.14

-UA

0.14

ehler

0.14

à¤Ŀ

0.14

 inertia

0.14

Activations Density 0.093%

aspects related to data processing performance in large datasets

No Known Activations