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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. 7-RES-JB
    11. 21631
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    Explanations

    phrases related to substantial quantities or intense situations

    oai_token-act-pair · gpt-3.5-turbo

    words related to magnitude or scale, particularly those that imply a large quantity or extent

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     elig
    -0.66
    ĺ
    -0.63
    making
    -0.62
    gnu
    -0.59
     Chr
    -0.59
     Schr
    -0.58
    obal
    -0.57
     solicitation
    -0.57
     Ãĸ
    -0.57
    ilater
    -0.57
    POSITIVE LOGITS
     amount
    0.84
     sized
    0.83
     doses
    0.81
    faith
    0.79
     circumst
    0.78
     amounts
    0.77
    æ©Ł
    0.74
    interesting
    0.72
    ordinary
    0.71
    dozen
    0.71
    Activations Density 0.174%

    No Known Activations