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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. 3-RES-JB
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    Explanations

    explicit mentions of 'facts'

    oai_token-act-pair · gpt-3.5-turbo

    the word "facts" and variations of it, indicating a focus on objective information and truth

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    yss
    -0.98
    osi
    -0.79
    ascus
    -0.79
    aeper
    -0.77
    isoft
    -0.76
    ergy
    -0.74
    asio
    -0.74
    ctic
    -0.73
    asus
    -0.73
    artney
    -0.72
    POSITIVE LOGITS
    facts
    1.06
     facts
    0.96
    heet
    0.87
    fact
    0.84
    fulness
    0.83
    Fact
    0.79
    ãĤ±
    0.79
     inacc
    0.78
    telling
    0.78
    ional
    0.76
    Activations Density 0.019%

    No Known Activations