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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. 9-RES-JB
    11. 10155
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    Explanations

    phrases describing intensity or emphasis

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating strong emphasis or intensity

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Mechdragon
    -0.67
     Cosponsors
    -0.64
     Compliance
    -0.64
     Credit
    -0.62
    soDeliveryDate
    -0.61
     Cipher
    -0.61
    inventoryQuantity
    -0.61
    luaj
    -0.61
     Landing
    -0.61
     Deng
    -0.61
    POSITIVE LOGITS
     uh
    0.89
     um
    0.85
    nery
    0.77
    ivably
    0.72
    ribly
    0.71
    itely
    0.70
     positively
    0.69
    really
    0.68
     VERY
    0.68
     ah
    0.68
    Activations Density 0.059%

    No Known Activations