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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. 1-RES-JB
    11. 8758
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    Explanations

    adjectives and verbs related to visualization or production, particularly in a digital or creative context

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "render" and its variations relating to visuals or representations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Chel
    -0.86
     Cly
    -0.82
    tar
    -0.71
    RH
    -0.70
    alg
    -0.69
    swick
    -0.68
    FTWARE
    -0.66
    hips
    -0.66
    CU
    -0.65
    overed
    -0.64
    POSITIVE LOGITS
     renders
    1.15
     render
    1.14
     rendered
    1.07
     rendering
    1.05
    rendered
    0.94
    render
    0.91
    senal
    0.87
     fide
    0.75
    ometimes
    0.75
     Render
    0.74
    Activations Density 0.012%

    No Known Activations