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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 17657
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    Explanations

    words related to creating obstacles or hindrances

    oai_token-act-pair · gpt-3.5-turbo

    terms related to obstruction and structure

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     thirds
    -0.77
     Lans
    -0.61
    butt
    -0.61
     bes
    -0.59
     Ole
    -0.58
    fare
    -0.57
     Giul
    -0.56
     Teresa
    -0.56
     Haram
    -0.56
     ashore
    -0.55
    POSITIVE LOGITS
    ions
    2.20
    ively
    2.20
    ive
    2.14
    ives
    2.00
    iveness
    1.80
    ivity
    1.79
    ible
    1.78
    ional
    1.75
    ivist
    1.72
    ors
    1.71
    Activations Density 0.195%

    No Known Activations