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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. 2-RES-JB
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    Explanations

    words related to potential future events or circumstances

    oai_token-act-pair · gpt-3.5-turbo

    terms related to contingency planning and unexpected situations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    orters
    -0.88
    Ģ
    -0.85
    eh
    -0.80
    Ĺ
    -0.79
    ķ
    -0.79
    Ķ
    -0.76
    ¶æ
    -0.74
    arb
    -0.74
    ulton
    -0.73
    ĵ
    -0.73
    POSITIVE LOGITS
     contingency
    1.35
     conting
    1.20
    plan
    0.89
     emergencies
    0.88
    ptoms
    0.83
     scenarios
    0.78
     planning
    0.77
     planners
    0.77
     wills
    0.77
     redundancy
    0.76
    Activations Density 0.012%

    No Known Activations