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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. 1-RES-JB
    11. 3163
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    Explanations

    words related to antagonists or villains in a narrative context

    oai_token-act-pair · gpt-3.5-turbo

    references to villains in storytelling and media

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    dating
    -0.75
    independent
    -0.75
    ordering
    -0.72
    olen
    -0.72
    ollen
    -0.71
    aternity
    -0.71
    kept
    -0.71
    press
    -0.71
    obar
    -0.68
    ensation
    -0.67
    POSITIVE LOGITS
     villain
    1.29
     villains
    1.09
     mastermind
    0.95
    ous
    0.87
     antagonist
    0.84
     Bane
    0.83
    esses
    0.78
     satir
    0.77
     strugg
    0.74
    hattan
    0.70
    Activations Density 0.009%

    No Known Activations