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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
    11. 24507
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    Explanations

    references to rituals or events involving grooming, such as grooming for a specific position or role, grooming the family dog, grooming for a particular event, and more

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "groom" and "bride" in various contexts related to weddings and ceremonies

    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
    odium
    -0.74
     Oo
    -0.67
     MacArthur
    -0.65
    obin
    -0.64
    SAY
    -0.64
    BILITIES
    -0.62
     Blessed
    -0.61
     Constitution
    -0.60
     contradiction
    -0.59
    peak
    -0.59
    POSITIVE LOGITS
     groom
    1.51
    xual
    1.03
    edIn
    0.89
    stakes
    0.88
     grooming
    0.86
    asus
    0.81
    eering
    0.81
     Bride
    0.81
    EStream
    0.80
    wra
    0.79
    Activations Density 0.007%

    No Known Activations