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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. 3-RES-JB
    11. 7137
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    Explanations

    keywords related to specific names and entities, specifically focusing on the presence of "Hir" and "Kod" in the processed text

    oai_token-act-pair · gpt-3.5-turbo

    proper nouns, specifically names of people and places

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    anwhile
    -0.82
    retty
    -0.77
    utical
    -0.69
    ãĤ¡
    -0.69
    qqa
    -0.68
    gemony
    -0.68
    @#&
    -0.68
    herty
    -0.67
    ylum
    -0.67
    ppard
    -0.65
    POSITIVE LOGITS
     Kod
    1.07
    uj
    0.91
    hiba
    0.88
     Hir
    0.85
    Rated
    0.84
     Jinn
    0.78
     Album
    0.76
    amic
    0.74
    rad
    0.72
    oka
    0.71
    Activations Density 0.015%

    No Known Activations