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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. 0-RES-JB
    11. 16674
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    Explanations

    key phrases related to drilling and monitoring wells, particularly in the context of environmental impact and resource extraction

    oai_token-act-pair · gpt-3.5-turbo

    references to wells and groundwater

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    urrency
    -0.70
    iveness
    -0.68
    cy
    -0.66
    utor
    -0.64
    ryan
    -0.62
    ce
    -0.62
    ion
    -0.62
    iu
    -0.62
    io
    -0.62
    ront
    -0.60
    POSITIVE LOGITS
     wells
    3.87
     reservoirs
    1.61
     ponds
    1.46
     pipelines
    1.43
     groundwater
    1.41
     dams
    1.28
     springs
    1.28
     earthquakes
    1.22
     barrels
    1.22
     fracking
    1.20
    Activations Density 0.007%

    No Known Activations