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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. 9-RES-JB
    6. 12086
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    INDEX
    Explanations

    persons wielding knives or being involved in knife-related actions or conflicts

    oai_token-act-pair · gpt-3.5-turbo

    references to knives and related actions or contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ICAN
    -0.84
    mberg
    -0.84
    bos
    -0.81
    ICLE
    -0.73
    rian
    -0.72
    ALS
    -0.71
    tainment
    -0.71
    oday
    -0.70
    leep
    -0.68
    tz
    -0.67
    POSITIVE LOGITS
     blades
    1.14
     blade
    1.12
     scissors
    1.05
     wielded
    1.03
     knives
    0.99
     knife
    0.94
    blade
    0.93
     wielding
    0.91
     dagger
    0.90
     claws
    0.89
    Activations Density 0.079%

    No Known Activations