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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. 24193
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    Explanations

    phrases emphasizing the beginning or initiation of actions or events

    oai_token-act-pair · gpt-3.5-turbo

    instances of the phrase "set in motion" or variations thereof

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    catentry
    -0.77
    inventoryQuantity
    -0.66
    akening
    -0.63
    urized
    -0.63
    iler
    -0.63
    ilege
    -0.61
    otten
    -0.61
    worthiness
    -0.61
    Kids
    -0.59
     qualified
    -0.59
    POSITIVE LOGITS
     abl
    0.91
    flame
    0.81
     stone
    0.81
    mberg
    0.80
    stone
    0.75
    Ń·
    0.65
    ¯¯¯¯
    0.64
     sails
    0.64
    alter
    0.63
    tle
    0.63
    Activations Density 0.063%

    No Known Activations