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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. 4-RES-JB
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    Explanations

    mentions of the beverage "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 @ 4-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.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.4.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    4
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ities
    -0.83
    izons
    -0.82
    osure
    -0.78
     WATCHED
    -0.76
    ibilities
    -0.76
    entric
    -0.74
    inations
    -0.72
    nesota
    -0.69
    SIGN
    -0.68
    alities
    -0.67
    POSITIVE LOGITS
     tea
    1.13
     towels
    1.08
     towel
    1.03
     drinkers
    0.97
    Tea
    0.95
    quila
    0.90
     kettle
    0.88
     Tea
    0.87
     cups
    0.86
    weed
    0.84
    Activations Density 0.004%

    No Known Activations