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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. 9-RES-JB
    11. 14164
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    Explanations

    phrases related to enjoyment or leisure activities

    oai_token-act-pair · gpt-3.5-turbo

    expressions of enjoyment and the concept of having a good time

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ural
    -0.70
     scrimmage
    -0.69
    pled
    -0.66
     Tycoon
    -0.65
    soDeliveryDate
    -0.65
    rawn
    -0.59
    pers
    -0.59
    omo
    -0.58
    gments
    -0.58
    arta
    -0.58
    POSITIVE LOGITS
     watching
    0.99
    ably
    0.89
     browsing
    0.86
     enjoying
    0.85
    lihood
    0.83
     chatting
    0.82
     listening
    0.80
     eating
    0.73
     enjoyment
    0.73
     Flavoring
    0.73
    Activations Density 0.055%

    No Known Activations