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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. 0-RES-JB
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    Explanations

    proper nouns consisting of "Ser" followed by a number

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "Ser" followed by numbers or names associated with individuals or entities

    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
    wagon
    -0.75
    taboola
    -0.73
    cott
    -0.69
    Keefe
    -0.67
     towed
    -0.67
    Michigan
    -0.66
     defund
    -0.66
    abc
    -0.66
    flower
    -0.66
    enegger
    -0.65
    POSITIVE LOGITS
     Ser
    3.95
    Ser
    2.68
     ser
    2.08
    ser
    1.66
     Serbian
    1.49
     SER
    1.42
     Serbia
    1.34
     Croat
    1.33
     Server
    1.24
     Seraph
    1.23
    Activations Density 0.012%

    No Known Activations