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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
0-RES-JB
3166
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0-res-jb
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Explanations
the word "Me" with varying degrees of emphasis indicated by activation strength
oai_token-act-pair · gpt-3.5-turbo
No Scores
the repetition of the word "Me"
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 @ 0-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
0
Activation Function
relu
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Negative Logits
UAL
-0.72
ctl
-0.66
icably
-0.65
flush
-0.65
acing
-0.64
flush
-0.63
ulative
-0.62
ript
-0.62
itiveness
-0.62
OWER
-0.60
POSITIVE LOGITS
Me
3.48
Me
2.45
ME
2.04
me
1.77
Us
1.49
Meh
1.41
ME
1.36
Him
1.33
My
1.27
me
1.24
Act
ivations
Density 0.012%
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