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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. 7-RES-JB
    11. 1592
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    Explanations

    phrases related to focusing attention or efforts

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to attention and focus

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
     Slip
    -0.61
     Athe
    -0.60
     stal
    -0.60
     photoc
    -0.56
     vending
    -0.55
     Pact
    -0.55
     Kirin
    -0.54
    --------------------
    -0.54
     signed
    -0.54
     Incredible
    -0.53
    POSITIVE LOGITS
     blame
    0.98
    vre
    0.94
     attention
    0.87
     Attention
    0.83
    phasis
    0.81
     energies
    0.78
     focus
    0.78
     emphasis
    0.77
     toward
    0.76
    orno
    0.76
    Activations Density 0.247%

    No Known Activations