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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. 8-RES-JB
    11. 2563
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    Explanations

    phrases related to directing attention towards a specific topic or action

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to prioritizing attention or resources

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    named
    -0.74
    OUGH
    -0.74
    BIT
    -0.72
    adding
    -0.71
    mia
    -0.71
    ania
    -0.68
    added
    -0.67
    idden
    -0.63
    mx
    -0.63
    anne
    -0.62
    POSITIVE LOGITS
    rite
    0.95
     focus
    0.86
     squarely
    0.82
    peed
    0.79
     attention
    0.79
     solely
    0.77
     toward
    0.77
     focused
    0.76
     foc
    0.75
     Attention
    0.74
    Activations Density 0.031%

    No Known Activations