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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
    11. 20180
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    Explanations

    mentions of specific brand names, particularly Starbucks

    oai_token-act-pair · gpt-3.5-turbo

    mentions of Starbucks and Walmart

    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
    ael
    -0.81
     ageing
    -0.66
    ffe
    -0.66
    Gra
    -0.66
     ele
    -0.66
    aceous
    -0.65
    iar
    -0.64
     prepar
    -0.64
    ead
    -0.63
     dra
    -0.63
    POSITIVE LOGITS
     Starbucks
    3.06
     Walmart
    2.93
     Costco
    2.40
     Lyft
    1.75
     Disneyland
    1.69
     Airbnb
    1.65
     Chevron
    1.62
     Subway
    1.59
     Staples
    1.59
     UPS
    1.52
    Activations Density 0.036%

    No Known Activations