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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. 12165
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    Explanations

    words related to specific groups or communities such as academia, wine industry, intelligence community, military, banking industry, Republican party, US, and Sri Lankan team

    oai_token-act-pair · gpt-3.5-turbo

    references to specific communities or groups

    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
    blem
    -0.82
    ignty
    -0.80
    tackle
    -0.73
    nil
    -0.73
    BILITIES
    -0.71
    quit
    -0.70
    ogram
    -0.70
    illac
    -0.69
    abel
    -0.69
    ograms
    -0.68
    POSITIVE LOGITS
     industry
    1.20
     media
    1.14
     mainstream
    1.13
     fanbase
    1.12
     profession
    1.07
     populace
    1.06
     halls
    1.05
     academy
    1.05
     periphery
    1.03
     audience
    1.02
    Activations Density 0.342%

    No Known Activations