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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. 3-RES-JB
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    Explanations

    mentions of the coffee company "Starbucks"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the Starbucks brand

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    uclear
    -0.72
    yss
    -0.69
     conting
    -0.65
    ologically
    -0.65
    ysis
    -0.64
    Reviewer
    -0.63
    othy
    -0.63
    onsense
    -0.62
     probabilities
    -0.62
    orse
    -0.61
    POSITIVE LOGITS
    bucks
    1.01
     Starbucks
    0.91
     cafe
    0.86
     caf
    0.81
     Stores
    0.81
     café
    0.80
    weed
    0.79
     Coffee
    0.79
     cafes
    0.78
     Restaur
    0.77
    Activations Density 0.006%

    No Known Activations