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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. 10-RES-JB
    11. 4420
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    Explanations

    references to loss or the negative impact of events or situations

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ECK
    -0.75
    ellar
    -0.69
     tee
    -0.67
     tranquil
    -0.65
     Aires
    -0.64
    ATT
    -0.63
    ENTS
    -0.62
    ULE
    -0.61
    ":[{"
    -0.61
    imen
    -0.61
    POSITIVE LOGITS
     aversion
    1.04
     incurred
    1.02
    luster
    1.01
    iem
    0.99
    esville
    0.91
    lust
    0.86
     suffered
    0.82
    nings
    0.82
     inflicted
    0.80
     Loss
    0.77
    Activations Density 0.053%

    No Known Activations