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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
    11. 3217
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    Explanations

    mentions of specific terms related to agriculture and crops, particularly "Ardent," "Rye," "Barley," and "Lakota."

    oai_token-act-pair · gpt-3.5-turbo

    specific brand or character names, particularly associated with alcoholic beverages

    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
    coni
    -0.85
    ulla
    -0.77
    ulhu
    -0.70
    ero
    -0.67
     sleeper
    -0.67
    unders
    -0.65
    riot
    -0.65
    ipeg
    -0.65
    Emb
    -0.63
    liness
    -0.63
    POSITIVE LOGITS
    ciples
    0.76
     Seym
    0.74
     Lak
    0.71
     whiskey
    0.70
    sembly
    0.68
    ds
    0.67
     Ard
    0.66
    itudinal
    0.66
    pas
    0.65
    pring
    0.65
    Activations Density 0.040%

    No Known Activations