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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. 6-RES-JB
    11. 15552
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    INDEX
    Explanations

    descriptions of individuals being trained or skilled in various professions or activities

    oai_token-act-pair · gpt-3.5-turbo

    words related to training and qualifications

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    FACE
    -0.77
     Skydragon
    -0.73
    ORED
    -0.69
    ween
    -0.66
    ptions
    -0.65
    $$$$
    -0.63
    Buzz
    -0.63
     sack
    -0.62
    adra
    -0.61
    orative
    -0.61
    POSITIVE LOGITS
     professionals
    0.84
     workforce
    0.82
     nursing
    0.82
    bodied
    0.79
     instructors
    0.79
     interpre
    0.76
     certific
    0.73
     trained
    0.73
    rentices
    0.72
    looking
    0.72
    Activations Density 0.056%

    No Known Activations