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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. 4-RES-JB
    11. 16501
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    Explanations

    phrases related to a large quantity or intensity

    oai_token-act-pair · gpt-3.5-turbo

    the word "much" and its variations or contexts indicating a significant amount or intensity

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

    No Comments

    Negative Logits
    İĭ
    -1.01
    pherd
    -0.84
    etts
    -0.81
    idon
    -0.77
    atures
    -0.76
    jamin
    -0.74
    ATURES
    -0.72
    pta
    -0.71
    othy
    -0.70
    stead
    -0.69
    POSITIVE LOGITS
    NESS
    0.82
     ado
    0.77
     effort
    0.76
     appreciated
    0.76
     else
    0.75
     dmg
    0.71
     interest
    0.69
     exposition
    0.67
     emphasis
    0.67
     damage
    0.66
    Activations Density 0.044%

    No Known Activations