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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. 4392
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    Explanations

    terms or phrases that emphasize or draw attention to specific elements, such as through highlighting or emphasizing

    oai_token-act-pair · gpt-3.5-turbo

    the word "highlight" and its variations in various contexts

    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
    thood
    -0.72
    cas
    -0.70
    itte
    -0.70
    nery
    -0.69
    entric
    -0.68
    atern
    -0.68
    aah
    -0.67
    onew
    -0.64
    zin
    -0.64
    ja
    -0.64
    POSITIVE LOGITS
     reel
    0.95
     highlights
    0.93
    ibilities
    0.79
    umenthal
    0.78
     highlighting
    0.76
    TextColor
    0.76
    ibility
    0.76
    OWS
    0.74
    iary
    0.74
     warnings
    0.71
    Activations Density 0.034%

    No Known Activations