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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. 4-RES-JB
    11. 16877
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    Explanations

    statements following patterns of 'A said that' or 'A wrote that' where the sequence 'âĢ/ľ' is usually present

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to counts or ratios involving significant issues or entities

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

    No Comments

    Negative Logits
    aukee
    -0.79
     disposal
    -0.70
     bounds
    -0.65
     adolesc
    -0.64
     gul
    -0.62
     obser
    -0.62
    izont
    -0.61
     amaz
    -0.61
     razor
    -0.60
     upgr
    -0.60
    POSITIVE LOGITS
    nob
    0.87
    they
    0.87
    someone
    0.81
    should
    0.75
    would
    0.73
    could
    0.72
    many
    0.71
    ķ
    0.70
    no
    0.69
    despite
    0.69
    Activations Density 0.266%

    No Known Activations