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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
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    Explanations

    mentions or instances of "tea"

    oai_token-act-pair · gpt-3.5-turbo

    references to tea

    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
    Vel
    -0.82
    plex
    -0.82
    gor
    -0.77
    alties
    -0.76
    atell
    -0.75
    Lev
    -0.75
     Predators
    -0.72
     Aut
    -0.71
     Vel
    -0.71
     Reflex
    -0.70
    POSITIVE LOGITS
     tea
    3.87
    Tea
    3.05
     Tea
    2.92
     coffee
    1.79
     espresso
    1.29
     Coffee
    1.28
     caffeine
    1.27
     breakfast
    1.23
     beverage
    1.21
     te
    1.21
    Activations Density 0.022%

    No Known Activations