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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. 7-RES-JB
    11. 2845
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    Explanations

    mentions of dietary habits and food consumption patterns

    oai_token-act-pair · gpt-3.5-turbo

    references to diet and dietary habits

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     bidding
    -0.72
     Dam
    -0.70
     Morse
    -0.67
     Patterson
    -0.66
     Templar
    -0.66
     Avalon
    -0.65
     Moff
    -0.65
     Stra
    -0.63
     Receiver
    -0.63
     Johann
    -0.62
    POSITIVE LOGITS
    etics
    1.22
    etic
    1.17
    eteria
    1.15
    rition
    1.07
    etically
    1.02
    onut
    0.95
     diet
    0.93
    namese
    0.92
     Coke
    0.92
    oleon
    0.87
    Activations Density 0.031%

    No Known Activations