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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. 15397
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    Explanations

    combinations of words that hint at causing harm or negative consequences

    oai_token-act-pair · gpt-3.5-turbo

    comma usage within complex sentence structures

    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
    ¬¼
    -0.63
    ety
    -0.58
    estones
    -0.53
    estone
    -0.50
    alogue
    -0.47
    ocl
    -0.45
    rack
    -0.45
    emaker
    -0.45
     redes
    -0.45
    orously
    -0.44
    POSITIVE LOGITS
     albeit
    0.86
     namely
    0.82
     although
    0.74
     including
    0.71
     aka
    0.70
     which
    0.70
     however
    0.65
     regardless
    0.65
     though
    0.64
     whereas
    0.64
    Activations Density 0.880%

    No Known Activations