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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

    adjectives related to thoroughness

    oai_token-act-pair · gpt-3.5-turbo

    references to thoroughness in actions or investigations

    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
    Not in Any Lists

    No Comments

    Negative Logits
    qqa
    -0.68
     Tonight
    -0.65
    oras
    -0.63
    artifacts
    -0.62
     Revenue
    -0.62
    dust
    -0.61
     Suc
    -0.60
    Tonight
    -0.60
     Moment
    -0.60
    ocene
    -0.60
    POSITIVE LOGITS
     thorough
    1.28
    bred
    1.14
    fare
    0.96
    ness
    0.89
    orough
    0.87
     acquaintance
    0.78
    nesses
    0.74
    rehensive
    0.73
    going
    0.73
     comprehensive
    0.72
    Activations Density 0.005%

    No Known Activations