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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. 1-RES-JB
    11. 23180
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    Explanations

    references to individuals or entities involved in creating or producing items, such as manufacturers or makers

    oai_token-act-pair · gpt-3.5-turbo

    words related to creators or producers in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     densely
    -0.67
     Territories
    -0.63
     Globe
    -0.63
     tears
    -0.63
    rises
    -0.61
     ski
    -0.60
     Rain
    -0.60
     WARRANT
    -0.59
     extrem
    -0.59
     Ground
    -0.58
    POSITIVE LOGITS
    maker
    1.28
    makers
    1.24
    Maker
    0.94
    warts
    0.87
    cham
    0.85
    ratulations
    0.85
     nomine
    0.85
     extraord
    0.84
    holder
    0.83
    atu
    0.81
    Activations Density 0.006%

    No Known Activations