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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. 7-RES-JB
    11. 14339
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    Explanations

    phrases emphasizing a significant amount or degree of something

    oai_token-act-pair · gpt-3.5-turbo

    phrases emphasizing the concept of quantity or abundance

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    pherd
    -0.87
    byn
    -0.74
    selves
    -0.74
    saf
    -0.74
    Ń·
    -0.72
    İĭ
    -0.71
    idon
    -0.69
    pta
    -0.68
    gart
    -0.67
    othy
    -0.67
    POSITIVE LOGITS
     firepower
    0.83
     hype
    0.78
    NESS
    0.76
     else
    0.75
     emotion
    0.75
     shit
    0.73
     crap
    0.72
     dmg
    0.72
     info
    0.70
     integrity
    0.70
    Activations Density 0.042%

    No Known Activations