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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. 7-RES-JB
    11. 10929
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    Explanations

    words related to workplace situations like memos, warnings, and office buildings

    oai_token-act-pair · gpt-3.5-turbo

    references to formal communication or warnings in a corporate context

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ãĥ´ãĤ¡
    -0.66
    Ö¼
    -0.65
    _.
    -0.63
    Insert
    -0.60
    Ö
    -0.60
    Attribute
    -0.57
     foundational
    -0.56
    ãĥ¼ãĥĨ
    -0.55
    å¤
    -0.55
    ONSORED
    -0.54
    POSITIVE LOGITS
    selves
    0.77
     their
    0.65
     evacuated
    0.63
     Their
    0.63
    their
    0.62
    ideshow
    0.60
    acas
    0.60
     tents
    0.60
     THEIR
    0.60
     backgrounds
    0.59
    Activations Density 1.322%

    No Known Activations