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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
    11. 23472
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    Explanations

    references to coffee-related words

    oai_token-act-pair · gpt-3.5-turbo

    references to coffee

    oai_token-act-pair · gpt-4o-miniTriggered 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
    Not in Any Lists

    No Comments

    Negative Logits
    oppable
    -0.80
    ROR
    -0.79
    yss
    -0.73
    alez
    -0.73
    avid
    -0.71
     Caldwell
    -0.68
    Filename
    -0.68
     newcom
    -0.63
     Eliot
    -0.63
    imedia
    -0.63
    POSITIVE LOGITS
     beans
    1.30
     Beans
    1.12
     bean
    1.10
     brewed
    1.03
     drinkers
    0.98
     cups
    0.95
     Bean
    0.90
     cup
    0.89
     shops
    0.89
     coffee
    0.88
    Activations Density 0.027%

    No Known Activations