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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

    the word "pull" with varying activation strengths

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "pull."

    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
    esan
    -0.73
    voy
    -0.69
    gran
    -0.67
    heid
    -0.67
    cussion
    -0.66
     Scope
    -0.65
    unic
    -0.65
    ecause
    -0.64
    isf
    -0.64
    ibel
    -0.64
    POSITIVE LOGITS
    pull
    1.23
     pull
    1.21
    Pull
    1.14
     Pull
    0.96
     pulls
    0.87
    lift
    0.85
     aggro
    0.85
     pulling
    0.79
     weeds
    0.78
     levers
    0.75
    Activations Density 0.011%

    No Known Activations