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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. 2420
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    Explanations

    medical conditions or related terms, specifically focusing on terms related to drug use and possession

    oai_token-act-pair · gpt-3.5-turbo

    references to drug paraphernalia

    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
     Decay
    -0.70
     reservation
    -0.69
     clock
    -0.68
    azeera
    -0.66
    ãĤ´ãĥ³
    -0.64
    zyk
    -0.60
    EStreamFrame
    -0.60
    CHR
    -0.58
    jong
    -0.57
    ayn
    -0.57
    POSITIVE LOGITS
    inarily
    0.79
    emort
    0.66
    olated
    0.65
    ante
    0.64
    intestinal
    0.63
    ãĥ´ãĤ¡
    0.62
    \<
    0.62
    ento
    0.61
    reddit
    0.61
    ancial
    0.60
    Activations Density 0.211%

    No Known Activations