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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
    11. 4932
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    Explanations

    percentages or proportions

    oai_token-act-pair · gpt-3.5-turbo

    references to statistical percentages

    oai_token-act-pair · gpt-4o-miniTriggered 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
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    No Comments

    Negative Logits
    ãĥ¤
    -0.75
    pload
    -0.71
    ITED
    -0.69
     obser
    -0.68
    ATHER
    -0.68
    ¯¯¯¯¯¯¯¯
    -0.67
    IRT
    -0.66
    kefeller
    -0.66
     detrim
    -0.65
    åİ
    -0.64
    POSITIVE LOGITS
    xual
    0.82
    iles
    0.79
    cake
    0.76
    imet
    0.75
    rated
    0.74
    imeter
    0.73
    rate
    0.73
     ABV
    0.72
     accuracy
    0.65
    ancy
    0.65
    Activations Density 0.058%

    No Known Activations