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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. 9932
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    Explanations

    keywords related to coffee shops or coffee-related activities

    oai_token-act-pair · gpt-3.5-turbo

    mentions of coffee and related establishments

    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
    ROR
    -0.88
    oppable
    -0.80
    orse
    -0.73
    lihood
    -0.71
    yss
    -0.70
    Filename
    -0.69
     Caldwell
    -0.68
    alez
    -0.66
    veh
    -0.66
    oral
    -0.66
    POSITIVE LOGITS
     beans
    1.23
     Beans
    1.09
     bean
    1.03
     brewed
    1.03
     drip
    0.95
     coffee
    0.91
     cups
    0.90
     drinkers
    0.87
     nap
    0.87
     laced
    0.85
    Activations Density 0.026%

    No Known Activations