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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    9. 0-RES-JB
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    Explanations

    instances of the word 'having' followed by a verb

    oai_token-act-pair · gpt-3.5-turbo

    phrases involving the word "having" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    iken
    -0.71
    bard
    -0.66
    ryu
    -0.65
    enge
    -0.61
    umes
    -0.61
     Trends
    -0.59
    ests
    -0.59
    ighter
    -0.59
    umin
    -0.58
    ura
    -0.58
    POSITIVE LOGITS
     having
    3.05
    having
    2.52
     needing
    1.98
     being
    1.78
     possessing
    1.76
     owning
    1.67
     Having
    1.66
    Having
    1.66
    being
    1.65
     knowing
    1.59
    Activations Density 0.030%

    No Known Activations