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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. 3248
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    Explanations

    keywords related to importance or necessity

    oai_token-act-pair · gpt-3.5-turbo

    phrases emphasizing the significance or critical nature of various subjects

    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
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    Negative Logits
    ILA
    -0.71
     Ended
    -0.69
    iverpool
    -0.67
    ategory
    -0.67
    ilk
    -0.66
     ç¥ŀ
    -0.59
    dor
    -0.59
    ById
    -0.59
    isle
    -0.58
    uthor
    -0.58
    POSITIVE LOGITS
     enough
    0.82
     nonetheless
    0.78
     to
    0.76
    ogical
    0.73
     that
    0.69
    ially
    0.65
     etiquette
    0.61
     emphas
    0.60
     reminder
    0.60
    IENT
    0.58
    Activations Density 0.059%

    No Known Activations