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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. 8-RES-JB
    11. 569
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    Explanations

    descriptions of research methodologies or techniques

    oai_token-act-pair · gpt-3.5-turbo

    statements about methodologies and their effectiveness

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ividual
    -0.88
     sqor
    -0.86
    enaries
    -0.78
    engers
    -0.74
    essage
    -0.71
     Signs
    -0.71
     Ezek
    -0.70
    aques
    -0.68
    arling
    -0.68
     sidx
    -0.67
    POSITIVE LOGITS
     whereby
    1.05
     practiced
    1.02
     devised
    0.99
     pioneered
    0.95
     perfected
    0.90
    ologies
    0.88
     employed
    0.86
     perm
    0.83
     recursive
    0.82
     adapted
    0.80
    Activations Density 0.691%

    No Known Activations