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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. 8-RES-JB
    11. 8098
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    Explanations

    information related to dietary habits and health recommendations

    oai_token-act-pair · gpt-3.5-turbo

    patterns related to dietary habits and food consumption

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     jurisd
    -0.89
     Torn
    -0.84
     Franch
    -0.82
     Franchise
    -0.81
    yrights
    -0.77
     ambig
    -0.77
     Inspector
    -0.75
     Constable
    -0.75
     franch
    -0.73
     Borders
    -0.71
    POSITIVE LOGITS
     diet
    1.60
     meals
    1.34
     calorie
    1.34
     diets
    1.33
     caloric
    1.31
     regimen
    1.29
     fasting
    1.26
     detox
    1.26
     aerobic
    1.24
     abstinence
    1.24
    Activations Density 0.756%

    No Known Activations