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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. 9-RES-JB
    11. 19718
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    Explanations

    references to manual or hands-on activities

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to manual labor and physical tasks

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ammy
    -0.74
     Glover
    -0.67
    eries
    -0.67
     Dwell
    -0.65
     Ing
    -0.64
     Emin
    -0.64
    ukong
    -0.62
    anic
    -0.60
     Osw
    -0.59
     Pend
    -0.59
    POSITIVE LOGITS
    aneously
    0.91
     cheaply
    0.89
     rather
    0.88
     instead
    0.87
     without
    0.80
     or
    0.77
    .$
    0.77
     using
    0.76
     basis
    0.76
     whenever
    0.75
    Activations Density 0.352%

    No Known Activations