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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
10-RES-JB
14765
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10-res-jb
Source/SAE
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Explanations
references to scientific and technical terms, possibly related to engineering, economics, or logistics
oai_token-act-pair · gpt-3.5-turbo
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connections to environmental issues and sustainability
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 @ 10-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
10
Activation Function
relu
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<iframe src="https://www.neuronpedia.org/gpt2-small/10-res-jb/14765?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true" title="Neuronpedia" style="height: 300px; width: 540px;"></iframe>
Link
https://www.neuronpedia.org/gpt2-small/10-res-jb/14765?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true
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Negative Logits
.).
-1.00
.''.
-0.96
%.
-0.84
+.
-0.80
`.
-0.78
"!
-0.77
.:
-0.74
.'
-0.73
.</
-0.72
.):
-0.67
POSITIVE LOGITS
,[
0.78
whilst
0.73
while
0.71
(),
0.71
whereas
0.68
but
0.68
("
0.66
&&
0.63
*/(
0.63
and
0.61
Act
ivations
Density 1.194%
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