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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. 11-RES-JB
    11. 12830
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    INDEX
    Explanations

    words related to successful and acclaimed works, particularly in the entertainment industry

    oai_token-act-pair · gpt-3.5-turbo

    keywords related to film production and success

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    Connector
    -0.86
    andum
    -0.73
    yip
    -0.73
    plementation
    -0.72
     [&
    -0.70
    clave
    -0.70
    Redditor
    -0.70
    pter
    -0.68
    fecture
    -0.68
    actionDate
    -0.67
    POSITIVE LOGITS
     films
    1.79
     movies
    1.68
     documentaries
    1.59
     titles
    1.57
     productions
    1.55
     classics
    1.55
     dramas
    1.54
     novels
    1.46
     sequels
    1.46
     franchises
    1.43
    Activations Density 0.372%

    No Known Activations