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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
8-RES-JB
7504
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8-res-jb
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Explanations
phrases related to machines or technical specifications
oai_token-act-pair · gpt-3.5-turbo
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oai_token-act-pair · gpt-4o-mini
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Avg Score: 68
New Auto-Interp
AutoInterp Type
claude-3-5-haiku-20241022
Generate
Top Features by Cosine Similarity
Comparing With
GPT2-SMALL @ 8-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
8
Activation Function
relu
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Default Test Text
IFrame
<iframe src=https://www.neuronpedia.org/gpt2-small/8-res-jb/7504?embed=true&embedexplanation=true&embedplots=true&embedtest=true" title="Neuronpedia" style="height: 300px; width: 540px;"></iframe>
Link
https://www.neuronpedia.org/gpt2-small/8-res-jb/7504?embed=true&embedexplanation=true&embedplots=true&embedtest=true
•
Prediction Features Layer 8 GPT2 Small
•
Examples of different Logit Weight Distributions - GPT2 Small Layer 8
Prediction Feature Example
•
Happy Hour
Prediction feature example
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Negative Logits
hra
-0.65
ria
-0.63
hex
-0.61
Teg
-0.61
alys
-0.60
unia
-0.59
agen
-0.59
aga
-0.59
hu
-0.59
js
-0.59
POSITIVE LOGITS
ING
1.65
ER
1.56
EST
1.55
URE
1.51
NING
1.49
LE
1.48
IES
1.48
ED
1.48
ERS
1.47
LIN
1.47
Act
ivations
Density 0.213%
Test
Steer
Stacked
Snippet
Full
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No Known Activations