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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. 7-RES-JB
    11. 8933
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    Explanations

    phrases related to enjoying or finding pleasure in various activities

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "enjoy" in various forms

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ural
    -0.72
    rawn
    -0.66
    raft
    -0.63
    soDeliveryDate
    -0.63
    pled
    -0.63
    ethical
    -0.62
    ene
    -0.61
     scrimmage
    -0.60
    ref
    -0.60
     mater
    -0.58
    POSITIVE LOGITS
    ably
    0.95
    lihood
    0.83
    nels
    0.79
     enjoyment
    0.78
    ĸļ
    0.78
    joy
    0.76
     enjoying
    0.76
     enjoys
    0.76
     watching
    0.74
    OWER
    0.71
    Activations Density 0.038%

    No Known Activations