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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. 4439
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    Explanations

    terms related to various types of liquids, especially broths, and specific food components

    oai_token-act-pair · gpt-3.5-turbo

    terms related to food and compartmentalization

    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
     mosqu
    -0.74
    vil
    -0.71
     metic
    -0.70
    uls
    -0.69
    pine
    -0.69
    awaru
    -0.68
     antit
    -0.68
     tyr
    -0.68
     unbeliev
    -0.67
     unnecess
    -0.66
    POSITIVE LOGITS
    éļ
    0.93
    java
    0.85
     Giov
    0.79
    lace
    0.79
     broth
    0.77
    SourceFile
    0.77
     Container
    0.75
    rand
    0.74
    ostic
    0.73
    gans
    0.73
    Activations Density 0.022%

    No Known Activations