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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. 1-RES-JB
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    Explanations

    mentions of different types of ammunition

    oai_token-act-pair · gpt-3.5-turbo

    references to ammunition and its quantities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    nee
    -0.85
    lihood
    -0.82
     Kier
    -0.73
    TH
    -0.72
    ŃĶ
    -0.72
    liness
    -0.71
    visible
    -0.71
    Wilson
    -0.70
    kj
    -0.70
    SEA
    -0.69
    POSITIVE LOGITS
     ammunition
    1.47
     ammo
    1.14
    munition
    1.10
     Ammunition
    1.08
     fodder
    0.99
     cartridges
    0.94
     flares
    0.89
     Ammo
    0.88
    andise
    0.86
     veter
    0.84
    Activations Density 0.018%

    No Known Activations