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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. 16669
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    Explanations

    phrases related to being on schedule or meeting timelines

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating progress or status towards a goal

    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
    ces
    -0.67
    opol
    -0.67
     Tsukuyomi
    -0.65
    yip
    -0.64
     Torn
    -0.64
    apore
    -0.63
    ggle
    -0.63
    uffle
    -0.61
    angles
    -0.59
    arthed
    -0.58
    POSITIVE LOGITS
     financially
    0.81
     academ
    0.78
     toward
    0.77
     towards
    0.74
     economically
    0.71
     footing
    0.68
     complying
    0.67
     antioxid
    0.66
     mentally
    0.66
     preparations
    0.65
    Activations Density 0.125%

    No Known Activations