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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. 15969
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    Explanations

    words related to specific objectives or goals

    oai_token-act-pair · gpt-3.5-turbo

    references to a specified target or objective

    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
    maid
    -0.72
    ãĥ©ãĥ³
    -0.69
    ooks
    -0.65
    IGH
    -0.65
    ModLoader
    -0.63
    ©¶æ
    -0.63
    ansk
    -0.62
    gian
    -0.62
     Expedition
    -0.62
    cia
    -0.62
    POSITIVE LOGITS
    ted
    1.28
    ting
    0.87
    topic
    0.78
    izen
    0.75
    ivity
    0.74
    ched
    0.71
     range
    0.71
    ivated
    0.71
    finder
    0.69
     audience
    0.69
    Activations Density 0.047%

    No Known Activations