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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. 1698
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    Explanations

    occurrences of falling or descending

    oai_token-act-pair · gpt-3.5-turbo

    situations involving falls or accidents

    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
    uncture
    -0.78
    otide
    -0.71
    actionDate
    -0.70
    algia
    -0.69
    PN
    -0.69
     saliva
    -0.68
    ufact
    -0.68
    ffect
    -0.67
    ochemistry
    -0.67
    earcher
    -0.67
    POSITIVE LOGITS
     cliffs
    1.49
     tallest
    1.47
     stairs
    1.35
     skysc
    1.33
     ceilings
    1.30
     cliff
    1.30
     tower
    1.25
     heights
    1.25
     towering
    1.21
     towers
    1.21
    Activations Density 0.309%

    No Known Activations