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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. 12-RES-JB
    11. 5055
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    Explanations

    information related to chemicals, specifically related to health risks, preparation methods, and equipment usage like grilling or smoking around food

    oai_token-act-pair · gpt-3.5-turbo
    Triggered by @bot

    terms related to health risks and food preparation processes

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 12-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.hook_resid_post
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.11.hook_resid_post
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
     pione
    -0.77
     withd
    -0.75
     encount
    -0.74
     destro
    -0.74
     unintention
    -0.74
     warr
    -0.73
    oreAnd
    -0.72
     glim
    -0.71
     oun
    -0.69
     occas
    -0.69
    POSITIVE LOGITS
     registering
    1.29
     raising
    1.28
     stopping
    1.26
     picking
    1.25
     placing
    1.23
     producing
    1.22
     returning
    1.22
     delivering
    1.22
     putting
    1.22
     calling
    1.21
    Activations Density 0.194%

    No Known Activations