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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. 10777
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    Explanations

    verbs related to getting ready or making arrangements

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to preparation for events or tasks

    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
    holes
    -0.76
    roma
    -0.75
    76561
    -0.68
    volent
    -0.65
    ochet
    -0.64
    $$$$
    -0.61
    ãĥĥãĥī
    -0.60
    hole
    -0.60
    utra
    -0.59
     Winged
    -0.57
    POSITIVE LOGITS
    itude
    0.88
    resses
    0.82
     beforehand
    0.77
     prepares
    0.76
     prepare
    0.75
     citiz
    0.74
    folios
    0.74
     Statements
    0.73
     SERV
    0.73
     meals
    0.73
    Activations Density 0.026%

    No Known Activations