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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. 3-RES-JB
    11. 11410
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    Explanations

    words related to negative consequences or harm

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "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 @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ansky
    -0.75
    ECK
    -0.74
    ENTS
    -0.74
     Caucas
    -0.69
     BELOW
    -0.67
    rouse
    -0.66
    ATT
    -0.65
    enegger
    -0.63
    kov
    -0.62
    raper
    -0.61
    POSITIVE LOGITS
     aversion
    1.01
     loss
    0.97
     Loss
    0.94
    iem
    0.90
    loss
    0.87
     losses
    0.81
     incurred
    0.80
    luster
    0.78
    front
    0.72
    ess
    0.69
    Activations Density 0.013%

    No Known Activations