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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. 10-RES-JB
    11. 10022
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    Explanations

    phrases related to goals and objectives

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to intentions, goals, and objectives

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    rete
    -0.67
     Fail
    -0.63
    azeera
    -0.61
    milo
    -0.58
    mite
    -0.56
     barriers
    -0.55
    paralle
    -0.54
    eries
    -0.53
    imore
    -0.53
    lio
    -0.53
    POSITIVE LOGITS
     goal
    0.75
     aim
    0.73
     being
    0.73
    idding
    0.69
     fostering
    0.68
     understanding
    0.68
     assisting
    0.66
     ensuring
    0.65
     improving
    0.65
     of
    0.65
    Activations Density 0.064%

    No Known Activations