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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 6-RES-JB
    6. 23181
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    Explanations

    phrases related to cause and effect

    oai_token-act-pair · gpt-3.5-turbo

    phrases that indicate causal relationships or conditions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    orn
    -0.71
    soDeliveryDate
    -0.69
    ELF
    -0.67
    quist
    -0.66
    IFIED
    -0.66
    OND
    -0.65
    HF
    -0.64
    ELD
    -0.64
    oph
    -0.63
    TERN
    -0.63
    POSITIVE LOGITS
     however
    0.92
     moreover
    0.82
     please
    0.70
     coupled
    0.69
     meanwhile
    0.66
     namely
    0.66
     chances
    0.65
     assum
    0.62
     whereby
    0.62
    dos
    0.62
    Activations Density 0.306%

    No Known Activations