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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. 22369
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    Explanations

    information related to social media engagement metrics such as views, followers, shares, and likes

    oai_token-act-pair · gpt-3.5-turbo

    metrics related to video popularity and social media engagement

    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
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    Negative Logits
     anat
    -0.74
    rugged
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     toug
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    bestos
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    displayText
    -0.71
    unta
    -0.68
    ilateral
    -0.68
     Romeo
    -0.67
     inherited
    -0.66
    obyl
    -0.66
    POSITIVE LOGITS
     Reddit
    1.14
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    1.12
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    1.06
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    1.05
     downloads
    1.03
     reddit
    1.03
     upload
    1.00
     spam
    1.00
     Alexa
    0.99
    Activations Density 0.948%

    No Known Activations