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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. 9122
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    Explanations

    references to different models, particularly focusing on mentioning the 'Model S', 'Model E', and 'Model T'

    oai_token-act-pair · gpt-3.5-turbo

    references to models and their classifications

    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
    azar
    -0.82
    omen
    -0.82
    ulhu
    -0.81
    cyclopedia
    -0.75
    kefeller
    -0.74
    èª
    -0.73
    OME
    -0.69
    omes
    -0.68
    olulu
    -0.67
    endo
    -0.67
    POSITIVE LOGITS
     organism
    0.88
    model
    0.75
    ered
    0.73
     Reloaded
    0.71
     Mayhem
    0.71
    er
    0.71
    models
    0.69
    etter
    0.69
    urer
    0.64
     organisms
    0.64
    Activations Density 0.044%

    No Known Activations