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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. 7-RES-JB
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    Explanations

    references to penalties in sports contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to penalties in sports contexts

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    yll
    -0.88
    atters
    -0.86
    pocket
    -0.86
    rina
    -0.79
    bian
    -0.75
     Remastered
    -0.74
    need
    -0.74
    bits
    -0.73
    âĸĪâĸĪâĸĪâĸĪ
    -0.73
    iry
    -0.72
    POSITIVE LOGITS
     levied
    0.97
     penalties
    0.93
     penalty
    0.91
     imposed
    0.91
     leveled
    0.87
     sanction
    0.79
     incurred
    0.79
     regimes
    0.76
     inflicted
    0.75
     killers
    0.74
    Activations Density 0.015%

    No Known Activations