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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. 22939
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    Explanations

    phrases related to legal and criminal activities

    oai_token-act-pair · gpt-3.5-turbo

    combinations of words that indicate incidents or events with associated numbers or details

    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
    Not in Any Lists

    No Comments

    Negative Logits
    igmatic
    -0.64
    grain
    -0.64
     geek
    -0.61
    ocl
    -0.61
    ":"/
    -0.60
    alogue
    -0.60
    reprene
    -0.60
    ¬¼
    -0.59
    erest
    -0.59
    ongevity
    -0.59
    POSITIVE LOGITS
     albeit
    1.05
     respectively
    1.04
     including
    1.01
     namely
    1.01
     citing
    0.99
     although
    0.95
     according
    0.93
     which
    0.88
     thereby
    0.86
     presumably
    0.85
    Activations Density 1.300%

    No Known Activations