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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. 5-RES-JB
    6. 15882
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    INDEX
    Explanations

    quantitative expressions of quantity or scale

    oai_token-act-pair · gpt-3.5-turbo

    phrases that include fractional quantities or measurements

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     appropri
    -0.66
     alloc
    -0.66
     bearer
    -0.64
     propri
    -0.64
    owicz
    -0.63
    PLA
    -0.61
    ADA
    -0.60
    amac
    -0.60
     uncond
    -0.59
     intrins
    -0.59
    POSITIVE LOGITS
    dozen
    0.96
     dozen
    0.85
    tails
    0.84
    hops
    0.78
     peeled
    0.74
    ousand
    0.72
    oil
    0.71
    agos
    0.70
    nir
    0.69
    assed
    0.69
    Activations Density 0.070%

    No Known Activations