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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. 16934
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    Explanations

    concepts related to frying, particularly in the context of cooking

    oai_token-act-pair · gpt-3.5-turbo

    words related to preparing food

    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
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    Negative Logits
    anooga
    -0.80
    irlf
    -0.75
    earable
    -0.71
    anas
    -0.71
    ovies
    -0.69
    awar
    -0.68
    iple
    -0.66
     inval
    -0.66
    ancial
    -0.65
    CVE
    -0.64
    POSITIVE LOGITS
    lander
    0.91
    stal
    0.88
    cks
    0.82
    EF
    0.80
    cker
    0.79
    stall
    0.78
    ries
    0.77
    ijn
    0.77
    vere
    0.75
    gaard
    0.74
    Activations Density 0.035%

    No Known Activations