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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. 5-RES-JB
    6. 11491
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    INDEX
    Explanations

    mentions or references to the front lines or engaging in direct action or confrontation

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to "front line" themes and contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    issions
    -0.82
    redited
    -0.74
    Pitt
    -0.72
    itt
    -0.72
    Arch
    -0.71
    Asset
    -0.71
    arth
    -0.70
    ission
    -0.69
    orig
    -0.69
    reditary
    -0.69
    POSITIVE LOGITS
     fighting
    0.91
    lines
    0.79
     frontline
    0.76
    roads
    0.73
    fighters
    0.72
    breaker
    0.71
     trenches
    0.71
     combating
    0.70
     lookout
    0.70
     Assassins
    0.68
    Activations Density 0.033%

    No Known Activations