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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. 2795
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    Explanations

    percentages and numbers

    oai_token-act-pair · gpt-3.5-turbo

    structured data, particularly involving statistical measures or percentages

    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
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    Negative Logits
     Catch
    -0.58
     tremend
    -0.58
     Montana
    -0.57
     Volunte
    -0.56
     Palmer
    -0.56
     Unle
    -0.55
     Serve
    -0.55
     Professional
    -0.54
     Kramer
    -0.54
     Monk
    -0.54
    POSITIVE LOGITS
    depending
    0.78
    endif
    0.77
    morrow
    0.69
     istg
    0.68
     respectively
    0.65
     versa
    0.64
    soDeliveryDate
    0.63
    istani
    0.63
    eco
    0.62
    âĵĺ
    0.61
    Activations Density 1.259%

    No Known Activations