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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
6-RES-JB
10007
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6-res-jb
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Explanations
phrases related to predictions, growth, and factual statements
oai_token-act-pair · gpt-3.5-turbo
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statements expressing predictions or assessments of potential outcomes
oai_token-act-pair · gpt-4o-mini
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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 @ 6-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
6
Activation Function
relu
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https://www.neuronpedia.org/gpt2-small/6-res-jb/10007?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true
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Negative Logits
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-0.73
.).
-0.70
).
-0.61
+.
-0.59
.)
-0.56
arthed
-0.56
).
-0.56
().
-0.56
.(
-0.55
%.
-0.55
POSITIVE LOGITS
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1.10
[
1.07
%"
1.05
,'"
0.96
.,"
0.92
â̦"
0.87
":
0.86
),"
0.85
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0.84
"
0.83
Act
ivations
Density 1.092%
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