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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. 9-RES-JB
    11. 23402
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    Explanations

    words related to strong emotions or emphasis

    oai_token-act-pair · gpt-3.5-turbo

    words related to eloquence and fervor

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     stripping
    -0.71
     redacted
    -0.68
     betray
    -0.68
     distraction
    -0.65
     miscarriage
    -0.63
     bump
    -0.62
     blur
    -0.62
     ado
    -0.62
     preferential
    -0.61
     censored
    -0.61
    POSITIVE LOGITS
    ency
    2.03
    ents
    1.92
    ently
    1.87
    ential
    1.86
    ences
    1.82
    encies
    1.82
    entially
    1.76
    ence
    1.73
    ent
    1.73
    iencies
    1.70
    Activations Density 0.142%

    No Known Activations