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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. 10-RES-JB
    11. 1048
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    Explanations

    phrases related to health risks and medical conditions

    oai_token-act-pair · gpt-3.5-turbo

    keywords related to health-related risks and food consumption

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    agus
    -0.76
     Faust
    -0.74
     Diet
    -0.73
    ector
    -0.69
     Witch
    -0.68
    argon
    -0.67
    gart
    -0.67
    ité
    -0.66
     Piet
    -0.66
     Houses
    -0.66
    POSITIVE LOGITS
     exceptionally
    0.87
     moderately
    0.83
     perfectly
    0.82
     extremely
    0.82
     realistically
    0.82
     unusually
    0.82
     extraordinarily
    0.80
     interestingly
    0.79
     undeniably
    0.79
     awfully
    0.79
    Activations Density 0.175%

    No Known Activations