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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. 4738
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    INDEX
    Explanations

    phrases related to negativity or severity

    oai_token-act-pair · gpt-3.5-turbo

    references to harsh conditions or realities

    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
    phis
    -0.93
    ovember
    -0.93
    ablish
    -0.85
    assies
    -0.81
    ĸļ
    -0.79
    cellent
    -0.74
    ITNESS
    -0.74
     Libraries
    -0.73
     Alive
    -0.73
    ilater
    -0.72
    POSITIVE LOGITS
     harsh
    1.11
     harshly
    0.95
    ness
    0.87
     harsher
    0.86
     punishment
    0.86
     punishments
    0.84
     contrasts
    0.83
     retribution
    0.83
    ened
    0.82
     hars
    0.81
    Activations Density 0.012%

    No Known Activations