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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. 2-RES-JB
    6. 12
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    Explanations

    the word "story" at different activation levels

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "story"

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    the noun "story"

    oai_token-act-pair · gpt-4-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inking
    -0.93
    avorite
    -0.93
    omin
    -0.90
    ignt
    -0.86
    omination
    -0.86
    elsius
    -0.84
    htaking
    -0.81
    inois
    -0.81
    orneys
    -0.80
    inence
    -0.80
    POSITIVE LOGITS
    telling
    0.93
    story
    0.88
     arc
    0.86
     revolving
    0.86
     Story
    0.86
     Stories
    0.86
     arcs
    0.85
     Reincarn
    0.84
     story
    0.84
    boards
    0.83
    Activations Density 0.039%

    No Known Activations