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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. 18635
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    Explanations

    a security or danger-related context, particularly related to physical harm or threat

    oai_token-act-pair · gpt-3.5-turbo

    words related to significant events or circumstances

    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
    imeters
    -0.71
    umbnails
    -0.69
    ibrary
    -0.68
    sequent
    -0.67
    arser
    -0.65
    ornings
    -0.65
    dozen
    -0.65
    neau
    -0.65
    arton
    -0.65
    xtap
    -0.65
    POSITIVE LOGITS
    !!!
    1.03
    !!!!
    1.03
    !!!!!
    1.02
    .....
    1.00
    ,,,,
    0.96
    !!"
    0.95
    ....
    0.93
    âĢ¦âĢ¦
    0.92
    ......
    0.92
     !!
    0.92
    Activations Density 1.583%

    No Known Activations