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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
9-RES-JB
8294
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MODEL
9-res-jb
Source/SAE
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Explanations
strong verbs and actions
oai_token-act-pair · gpt-3.5-turbo
No Scores
phrases involving variations of the word "up."
oai_token-act-pair · gpt-4o-mini
Triggered by @bot
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New Auto-Interp
AutoInterp Type
claude-4-5-haiku
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Top Features by Cosine Similarity
Comparing With
GPT2-SMALL @ 9-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.hook_resid_pre
How To Load
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
9
Activation Function
relu
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https://www.neuronpedia.org/gpt2-small/9-res-jb/8294?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true
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Negative Logits
ici
-0.75
illi
-0.73
rit
-0.71
illian
-0.69
ĸļ
-0.69
IFA
-0.65
Farmers
-0.65
Mann
-0.64
ori
-0.64
Mutual
-0.64
POSITIVE LOGITS
up
1.69
up
1.56
Up
1.48
UP
1.46
ups
1.44
Up
1.38
UP
1.35
ups
1.31
down
1.23
down
1.16
Act
ivations
Density 0.109%
Test
Steer
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