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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. 3-RES-JB
    11. 16781
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    Explanations

    mentions of different types of soups

    oai_token-act-pair · gpt-3.5-turbo

    mentions of soup in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inel
    -0.67
    uate
    -0.67
    oral
    -0.65
     Freem
    -0.64
    sburg
    -0.63
    rium
    -0.62
    âĢ¢âĢ¢âĢ¢âĢ¢
    -0.60
    tg
    -0.60
     Planetary
    -0.59
    unknown
    -0.59
    POSITIVE LOGITS
     soup
    1.42
     Soup
    1.28
    bowl
    1.00
     kitchens
    0.99
     broth
    0.92
    ée
    0.85
     nood
    0.85
     kettle
    0.83
     sou
    0.83
     bowls
    0.82
    Activations Density 0.007%

    No Known Activations