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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. 4-RES-JB
    11. 4664
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    Explanations

    mentions of firearms or criminal activity involving guns

    oai_token-act-pair · gpt-3.5-turbo

    repeated mentions of "gunman" and "gunmen" in contexts related to violent incidents

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

    No Comments

    Negative Logits
     Grid
    -0.80
    âĶĢâĶĢâĶĢâĶĢ
    -0.78
    rates
    -0.74
    Champ
    -0.73
    McC
    -0.71
    Rate
    -0.70
    Recommend
    -0.70
    Vert
    -0.70
    amins
    -0.67
    Weather
    -0.67
    POSITIVE LOGITS
     gunman
    1.00
     gunmen
    0.92
     wielding
    0.91
     gunned
    0.86
     assassinated
    0.83
     assailant
    0.80
    abwe
    0.76
     murdered
    0.73
    powder
    0.73
     hijacked
    0.73
    Activations Density 0.016%

    No Known Activations