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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. 17055
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    Explanations

    phrases related to medical treatments or experiments

    oai_token-act-pair · gpt-3.5-turbo

    aspects related to experimental methods and participant responses

    oai_token-act-pair · gpt-4o-miniTriggered 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
    Not in Any Lists

    No Comments

    Negative Logits
    redo
    -0.76
    inventoryQuantity
    -0.66
    deal
    -0.66
    irl
    -0.65
    soDeliveryDate
    -0.64
     Ambrose
    -0.63
    Lv
    -0.62
     escapes
    -0.62
     Celt
    -0.62
    âĿ
    -0.61
    POSITIVE LOGITS
     placebo
    1.19
     randomly
    1.17
    Particip
    1.11
     questionnaire
    1.10
     participants
    1.06
     simulated
    1.04
     Participants
    1.02
     randomized
    1.02
    particip
    0.96
    naires
    0.96
    Activations Density 0.431%

    No Known Activations