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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. 17690
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    INDEX
    Explanations

    phrases emphasizing a high degree or intensity of something

    oai_token-act-pair · gpt-3.5-turbo

    intensifiers or exaggerative phrases

    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
     councils
    -0.77
     workshops
    -0.73
     panels
    -0.73
     assemblies
    -0.72
    eworks
    -0.72
     segments
    -0.72
     interfaces
    -0.70
    ensions
    -0.70
     Contracts
    -0.69
    atives
    -0.69
    POSITIVE LOGITS
     lot
    0.83
    swer
    0.75
    ozy
    0.73
     bunch
    0.68
    few
    0.68
    load
    0.68
     couple
    0.68
    lot
    0.68
     approximation
    0.67
    fer
    0.67
    Activations Density 0.426%

    No Known Activations