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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
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    Explanations

    references to food and related activities

    oai_token-act-pair · gpt-3.5-turbo

    references to food-related activities and their context

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    billion
    -0.74
    maxwell
    -0.71
    udic
    -0.64
    mega
    -0.64
     teasp
    -0.62
     franch
    -0.60
     publishing
    -0.58
     plagiar
    -0.58
    arlane
    -0.58
     AMER
    -0.56
    POSITIVE LOGITS
     thereafter
    0.74
     afterwards
    0.72
     underneath
    0.70
     ensued
    0.69
     preceded
    0.68
     supplemented
    0.66
    SPONSORED
    0.64
     upstairs
    0.63
    eers
    0.62
     ItemLevel
    0.61
    Activations Density 0.715%

    No Known Activations