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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. 6-RES-JB
    6. 12028
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    Explanations

    instances where an emphasis is placed on the quantity or extent of something

    oai_token-act-pair · gpt-3.5-turbo

    repetitions of the word "much" and expressions of degree or quantity

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    thumbnails
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    imens
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    perse
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    æ©Ł
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    Interstitial
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    details
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    inen
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    lets
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    IVERS
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    POSITIVE LOGITS
    OTAL
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     Ballard
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    efeated
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    });
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     fide
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    ange
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    emark
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    cture
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     Keane
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     anymore
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    Activations Density 0.110%

    No Known Activations