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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. 3-RES-JB
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    Explanations

    references to movie theaters or cinema venues

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "cinema" and its variations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    lies
    -0.73
    */(
    -0.72
    legged
    -0.70
    nesses
    -0.68
    egg
    -0.68
    lying
    -0.66
    lynn
    -0.66
    hips
    -0.66
    ciating
    -0.65
    tnc
    -0.64
    POSITIVE LOGITS
     cinema
    1.00
    goers
    0.88
     Cinema
    0.88
    ovies
    0.85
     cinem
    0.83
     theaters
    0.83
     buffs
    0.79
    umbai
    0.78
    isoft
    0.78
     marqu
    0.75
    Activations Density 0.012%

    No Known Activations