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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. 5553
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    Explanations

    references to wood material

    oai_token-act-pair · gpt-3.5-turbo

    mentions of wood and its various contexts or uses

    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
    Not in Any Lists

    No Comments

    Negative Logits
    uberty
    -0.74
     aver
    -0.71
     Fren
    -0.71
    orsche
    -0.68
     Merkel
    -0.66
     Sunshine
    -0.66
    OPLE
    -0.65
    ONT
    -0.64
    ochet
    -0.64
    HM
    -0.64
    POSITIVE LOGITS
    working
    1.10
    wood
    1.01
    worker
    1.01
     pulp
    0.98
    blocks
    0.95
    wind
    0.94
    ruff
    0.94
    work
    0.94
    lands
    0.93
    bats
    0.93
    Activations Density 0.019%

    No Known Activations