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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. 0-RES-JB
    11. 22753
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    Explanations

    words or phrases related to being subjected to various actions or conditions

    oai_token-act-pair · gpt-3.5-turbo

    instances of being subjected to various forms of treatment or experiences, often negative in nature

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     Vegas
    -0.73
     Vision
    -0.69
    draw
    -0.67
    ashi
    -0.66
     vision
    -0.65
     Horizon
    -0.64
    mir
    -0.63
     map
    -0.60
     Victory
    -0.60
     Play
    -0.60
    POSITIVE LOGITS
     subjected
    3.36
     deprived
    1.43
     interrogated
    1.41
     treated
    1.34
     exposed
    1.34
     hurled
    1.26
     undergoing
    1.25
     subject
    1.24
     discriminated
    1.23
     harassed
    1.21
    Activations Density 0.017%

    No Known Activations