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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. 17793
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    Explanations

    descriptions or mentions of high-resolution display specifications

    oai_token-act-pair · gpt-3.5-turbo

    terms related to video or image resolution

    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
    redo
    -0.95
    doms
    -0.80
    obin
    -0.80
    bara
    -0.78
    spring
    -0.77
    bons
    -0.77
    odor
    -0.76
    tail
    -0.75
    soDeliveryDate
    -0.73
    odge
    -0.73
    POSITIVE LOGITS
     resolution
    0.91
     resolutions
    0.81
     mismatch
    0.81
     scale
    0.78
     Imaging
    0.74
     Resolution
    0.73
     creep
    0.72
     1440
    0.70
     scaling
    0.70
     sickness
    0.70
    Activations Density 0.018%

    No Known Activations