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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
    11. 1222
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    Explanations

    words related to negative circumstances or events

    oai_token-act-pair · gpt-3.5-turbo

    suffixes related to negative outcomes or consequences

    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
    ovych
    -0.75
    liners
    -0.65
    hunt
    -0.62
     Ans
    -0.61
     trump
    -0.59
    ighter
    -0.59
    ebook
    -0.58
    hoff
    -0.58
     prey
    -0.57
     Houses
    -0.57
    POSITIVE LOGITS
    uration
    0.86
    ãĤ¼ãĤ¦ãĤ¹
    0.86
    rency
    0.77
    enza
    0.77
    inence
    0.76
    ado
    0.76
    ruct
    0.74
    ATED
    0.71
    LECT
    0.69
    ña
    0.69
    Activations Density 0.066%

    No Known Activations