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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. 6-RES-JB
    11. 4321
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    Explanations

    words related to preparation, anticipation, honor, view, terms, spirit, regards, celebration, consideration, interest, answer, tune, and response

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating preparation, anticipation, or consideration for upcoming events or actions

    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
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     mustard
    -0.59
    aja
    -0.58
     ..."
    -0.57
    JUST
    -0.55
    "},"
    -0.54
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    Activations Density 0.097%

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