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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. 2231
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    Explanations

    words related to achieving goals and being successful

    oai_token-act-pair · gpt-3.5-turbo

    references to success in various contexts

    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
     pores
    -0.66
    Earth
    -0.63
     ox
    -0.62
    Natural
    -0.62
    electric
    -0.62
     iodine
    -0.61
     weights
    -0.61
     onions
    -0.60
    Electric
    -0.60
     cables
    -0.60
    POSITIVE LOGITS
    ively
    0.87
    fully
    0.85
    iation
    0.82
    iated
    0.79
    ulence
    0.76
    ceed
    0.75
    awaru
    0.75
    ace
    0.74
    uates
    0.74
     success
    0.74
    Activations Density 0.022%

    No Known Activations