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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. 2-RES-JB
    11. 14354
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    Explanations

    terms associated with the brewing industry and process

    oai_token-act-pair · gpt-3.5-turbo

    terms related to the brewing process and industry

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    olphins
    -0.97
    orse
    -0.89
    obo
    -0.82
    earchers
    -0.81
    ciating
    -0.78
    eah
    -0.78
    graded
    -0.75
    orses
    -0.75
    phis
    -0.75
    cellence
    -0.74
    POSITIVE LOGITS
     brewed
    1.22
     brewing
    1.14
     brewer
    1.12
     brewers
    1.04
    Brew
    0.95
     brew
    0.84
    Beer
    0.83
     malt
    0.81
     brewery
    0.81
     yeast
    0.81
    Activations Density 0.011%

    No Known Activations