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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
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    Explanations

    references to a specific sports team, specifically the "Tigers"

    oai_token-act-pair · gpt-3.5-turbo

    references to the Tigers baseball team

    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
    iture
    -0.87
    trak
    -0.78
    roximately
    -0.73
    inventoryQuantity
    -0.72
    Ïĥ
    -0.71
    itures
    -0.70
    uters
    -0.69
    aleigh
    -0.69
    buquerque
    -0.69
     Koen
    -0.66
    POSITIVE LOGITS
     Tigers
    1.31
     Tiger
    0.84
    emonium
    0.82
     tigers
    0.76
     resil
    0.72
    bol
    0.71
     Pistons
    0.68
     Unleashed
    0.68
     tiger
    0.68
    igers
    0.68
    Activations Density 0.009%

    No Known Activations