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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. 10-RES-JB
    11. 4350
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    Explanations

    the text related to cooking and food preparation

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to smoke, heat, and their effects on food and environment

    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
    emale
    -0.79
    ĸļ
    -0.78
     oun
    -0.72
    tein
    -0.71
    ©¶æ
    -0.70
    ccording
    -0.68
    ñ
    -0.66
    ĻĤ
    -0.65
    ¿½
    -0.65
    Nitrome
    -0.64
    POSITIVE LOGITS
     abnormalities
    0.61
     attRot
    0.57
    .'"
    0.56
    âĢ¦"
    0.56
    ..."
    0.56
     Stealth
    0.54
     }
    0.54
    !'
    0.54
    !'"
    0.54
    .'
    0.54
    Activations Density 0.146%

    No Known Activations