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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 8762
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    Explanations

    phrases related to suffering or health issues

    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
     Collider
    -0.75
    hens
    -0.68
    onomy
    -0.68
    TRY
    -0.66
    clusive
    -0.65
    amera
    -0.64
    tarians
    -0.64
    ouf
    -0.64
    uese
    -0.63
    appro
    -0.63
    POSITIVE LOGITS
     setbacks
    1.15
     losses
    1.08
     fools
    1.00
     terribly
    0.98
     debilitating
    0.96
     horrend
    0.95
     severe
    0.93
     horribly
    0.93
     embarrassment
    0.91
     injuries
    0.91
    Activations Density 0.058%

    No Known Activations