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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. 12891
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    Explanations

    references to different types of alcoholic beverages, particularly wines

    oai_token-act-pair · gpt-3.5-turbo

    references to wine and wine-related terminology

    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
    aneously
    -0.87
    aneous
    -0.85
    urtle
    -0.72
    uled
    -0.71
    uli
    -0.68
    adden
    -0.68
    urat
    -0.68
    pta
    -0.68
    rencies
    -0.68
    ulation
    -0.68
    POSITIVE LOGITS
     vinegar
    1.12
     tasting
    1.12
     grapes
    1.05
     wine
    1.02
     cellar
    0.96
     tast
    0.93
    wine
    0.92
     grape
    0.87
     vine
    0.87
     wines
    0.86
    Activations Density 0.025%

    No Known Activations