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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. 8588
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    Explanations

    words related to negative emotions or consequences, specifically focusing on the concept of loss

    oai_token-act-pair · gpt-3.5-turbo

    references to the concept of loss 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
    ansky
    -0.80
    ENTS
    -0.79
    ATT
    -0.71
    ECK
    -0.69
    chell
    -0.67
    kov
    -0.67
    enegger
    -0.65
     BELOW
    -0.64
     Caucas
    -0.64
     inventive
    -0.63
    POSITIVE LOGITS
     aversion
    0.91
     loss
    0.88
    iem
    0.88
     Loss
    0.87
     incurred
    0.84
    luster
    0.76
    front
    0.76
    loss
    0.76
     losses
    0.73
    esville
    0.68
    Activations Density 0.016%

    No Known Activations