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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. 10050
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    INDEX
    Explanations

    references to various types of exposure, such as environmental, medical, and occupational exposure

    oai_token-act-pair · gpt-3.5-turbo

    references to environmental exposure and its effects

    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
    notations
    -0.73
    reme
    -0.73
    assian
    -0.70
     Kou
    -0.69
    eteenth
    -0.68
    aws
    -0.67
    ifully
    -0.66
    rocal
    -0.66
    rolley
    -0.66
    baum
    -0.66
    POSITIVE LOGITS
    ibilities
    0.86
     Exposure
    0.84
    é¾
    0.82
     thereto
    0.81
    801
    0.74
     exposure
    0.73
     exposures
    0.73
    IBLE
    0.73
     incurred
    0.72
    в
    0.70
    Activations Density 0.038%

    No Known Activations