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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
    11. 3055
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    Explanations

    words related to difficult or challenging situations

    oai_token-act-pair · gpt-3.5-turbo

    the term "rough" in various contexts

    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
    ensional
    -0.78
    merce
    -0.76
    uality
    -0.74
    Fram
    -0.74
    itutional
    -0.72
    amus
    -0.72
    iphate
    -0.70
    mberg
    -0.70
    natureconservancy
    -0.70
    alian
    -0.70
    POSITIVE LOGITS
     rough
    0.91
     edges
    0.87
    hed
    0.73
    ãģį
    0.71
    casts
    0.70
     sketch
    0.69
     corners
    0.69
    cut
    0.69
     Rough
    0.69
    neck
    0.69
    Activations Density 0.006%

    No Known Activations