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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 2-RES-JB
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    Explanations

    mentions of aerial activities and operations such as surveillance, bombing, reconnaissance, and drones

    oai_token-act-pair · gpt-3.5-turbo

    terms related to aerial operations and surveillance

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    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
    esson
    -0.97
    士
    -0.82
    ublic
    -0.73
    etts
    -0.73
    regon
    -0.71
    shire
    -0.71
    utical
    -0.70
    essee
    -0.69
    aunder
    -0.69
    hood
    -0.67
    POSITIVE LOGITS
     aerial
    1.17
    plane
    1.01
     reconnaissance
    0.91
     Aerial
    0.89
     spraying
    0.89
     refuel
    0.88
    planes
    0.86
     drones
    0.81
     photography
    0.79
     flights
    0.78
    Activations Density 0.009%

    No Known Activations