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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 1-RES-JB
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    Explanations

    instances of the word "arrests" with varying degrees of intensity

    oai_token-act-pair · gpt-3.5-turbo

    references to arrests

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    yss
    -0.67
     corridor
    -0.64
     regener
    -0.63
     reservoir
    -0.59
     Myth
    -0.58
    vironment
    -0.58
    psons
    -0.58
     Valley
    -0.57
    WE
    -0.56
     parachute
    -0.56
    POSITIVE LOGITS
     arrests
    1.08
     arrest
    0.86
     arrested
    0.84
     Rohing
    0.80
    enance
    0.76
     Arrest
    0.75
    onto
    0.74
     apprehended
    0.74
    è»
    0.73
    oppable
    0.73
    Activations Density 0.008%

    No Known Activations