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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

    proper nouns related to locations in Bavaria

    oai_token-act-pair · gpt-3.5-turbo

    references to Bavaria and associated regions, specifically focusing on sports and organizations

    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
    owder
    -0.80
    skinned
    -0.76
    --------------------------------
    -0.76
    lled
    -0.73
    LECT
    -0.69
    ented
    -0.66
    ::::::::
    -0.66
    motion
    -0.65
    ----------------
    -0.65
    ------------------------------------------------
    -0.65
    POSITIVE LOGITS
     Munich
    1.41
     Mü
    1.21
     Bav
    1.05
     Dortmund
    1.01
     Bayern
    0.94
     Bundesliga
    0.92
    hof
    0.89
    stadt
    0.87
    liga
    0.84
    alis
    0.84
    Activations Density 0.008%

    No Known Activations