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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
4131
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MODEL
10-res-jb
Source/SAE
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oai_token-act-pair · gpt-3.5-turbo
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elements of medical and educational institutions or examinations
oai_token-act-pair · gpt-4o-mini
Triggered by @bot
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New Auto-Interp
AutoInterp Type
claude-3-5-haiku-20241022
Generate
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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Default Test Text
IFrame
<iframe src=https://www.neuronpedia.org/gpt2-small/10-res-jb/4131?embed=true&embedexplanation=true&embedplots=true&embedtest=true" title="Neuronpedia" style="height: 300px; width: 540px;"></iframe>
Link
https://www.neuronpedia.org/gpt2-small/10-res-jb/4131?embed=true&embedexplanation=true&embedplots=true&embedtest=true
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Negative Logits
ģ«
-0.80
Zhao
-0.79
marqu
-0.79
Boll
-0.75
prol
-0.72
Ambro
-0.71
ober
-0.70
illon
-0.70
Dion
-0.69
Marqu
-0.69
POSITIVE LOGITS
SS
1.37
S
1.28
SA
1.19
SS
1.19
SR
1.19
sg
1.13
Samp
1.12
SE
1.10
SG
1.10
S
1.10
Act
ivations
Density 0.766%
Test
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