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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. 9-RES-JB
    11. 23639
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    Explanations

    words related to high quality or excellence

    oai_token-act-pair · gpt-3.5-turbo

    terms related to high quality or excellence

    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
    walk
    -0.81
    NetMessage
    -0.71
    Ey
    -0.71
    gren
    -0.69
    Mart
    -0.67
    cling
    -0.65
    SEE
    -0.65
    Lean
    -0.64
    soDeliveryDate
    -0.64
    gat
    -0.64
    POSITIVE LOGITS
    itude
    0.87
     quality
    0.85
     achievement
    0.85
     teamwork
    0.83
     performances
    0.81
     rendition
    0.81
     qualities
    0.80
     performance
    0.80
     accomplishment
    0.79
    iated
    0.79
    Activations Density 0.100%

    No Known Activations