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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. 6-RES-JB
    11. 15333
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    Explanations

    sports-related events and activities

    oai_token-act-pair · gpt-3.5-turbo

    punctuation marks, specifically commas

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    yll
    -0.90
    onym
    -0.76
    reprene
    -0.75
    sylv
    -0.72
    erb
    -0.70
    orno
    -0.70
    sth
    -0.69
    riet
    -0.68
    inar
    -0.67
    inates
    -0.65
    POSITIVE LOGITS
     albeit
    0.91
     namely
    0.86
     coached
    0.83
     finishing
    0.79
     Bengals
    0.79
     although
    0.78
     beating
    0.77
     teammate
    0.76
     scoring
    0.76
     rookie
    0.76
    Activations Density 0.322%

    No Known Activations