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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

    mentions of the word "Squ" in the text

    oai_token-act-pair · gpt-3.5-turbo

    references to squats and related terminology

    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
    odiac
    -0.70
     conductor
    -0.68
    ahan
    -0.67
    ibles
    -0.65
    ibi
    -0.63
    kson
    -0.63
     cognition
    -0.62
     presumed
    -0.62
     museum
    -0.61
    IAS
    -0.61
    POSITIVE LOGITS
     Squ
    3.55
    Squ
    3.41
    squ
    3.17
     SQU
    2.22
     squats
    1.91
     squat
    1.82
     squ
    1.78
     Squid
    1.76
     squash
    1.73
     Squirrel
    1.37
    Activations Density 0.016%

    No Known Activations