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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. 4-RES-JB
    11. 13570
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    Explanations

    phrases related to bringing or taking something/someone

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "bring" and its variations

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

    No Comments

    Negative Logits
    schild
    -0.84
    dating
    -0.81
    livious
    -0.73
    uchs
    -0.69
    doms
    -0.68
     Lumpur
    -0.68
    debian
    -0.66
    roman
    -0.65
    burst
    -0.64
     Skydragon
    -0.62
    POSITIVE LOGITS
     forth
    0.96
    bring
    0.84
     forward
    0.76
     together
    0.71
     guests
    0.71
    glers
    0.69
    ugu
    0.68
    backs
    0.68
     largeDownload
    0.66
    engers
    0.66
    Activations Density 0.032%

    No Known Activations