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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. 1-RES-JB
    6. 17499
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    Explanations

    mentions of being impressed or impressed by something/someone

    oai_token-act-pair · gpt-3.5-turbo

    expressions of admiration or being impressed

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    turn
    -0.69
    access
    -0.68
    rama
    -0.68
    violence
    -0.67
     extraction
    -0.67
     diverted
    -0.63
     abort
    -0.61
    leasing
    -0.61
    population
    -0.61
    build
    -0.61
    POSITIVE LOGITS
     impressed
    1.15
     resemb
    0.85
    sson
    0.76
     Wenger
    0.74
     surprised
    0.73
    MENTS
    0.71
    acebook
    0.69
     admire
    0.69
    oresc
    0.69
    GGGGGGGG
    0.69
    Activations Density 0.009%

    No Known Activations