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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. 24558
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    Explanations

    words related to directional trends, specifically focusing on words related to upward trends

    oai_token-act-pair · gpt-3.5-turbo

    words related to trends in data, specifically indicating upward or downward movements

    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
    abase
    -0.94
    DN
    -0.83
    TOP
    -0.78
    ghazi
    -0.73
    mberg
    -0.67
    illon
    -0.67
    imens
    -0.66
     ashore
    -0.66
    berman
    -0.66
    ergus
    -0.65
    POSITIVE LOGITS
     spiral
    0.99
     trajectory
    0.95
     traject
    0.89
     pressure
    0.84
     Spiral
    0.83
     curv
    0.81
    most
    0.80
    volent
    0.80
     revisions
    0.79
    clair
    0.79
    Activations Density 0.042%

    No Known Activations