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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. 9-RES-JB
    11. 13941
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    Explanations

    individuals with specific characteristics or conditions, such as medical illnesses, sensory sensitivities, or disadvantaged circumstances

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "have" and its variations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ensing
    -0.69
    xe
    -0.65
    quote
    -0.65
    alyst
    -0.64
    idding
    -0.64
     fray
    -0.63
    etting
    -0.62
     Recap
    -0.61
     guiName
    -0.60
    using
    -0.59
    POSITIVE LOGITS
     undergone
    1.33
     been
    1.27
    been
    1.09
     gotten
    1.04
     suffered
    1.01
     gone
    1.00
     disabilities
    0.99
     eaten
    0.96
     endured
    0.95
     aspirations
    0.93
    Activations Density 0.360%

    No Known Activations