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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. 22665
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    Explanations

    words related to roughness or difficulty

    oai_token-act-pair · gpt-3.5-turbo

    references to challenges or difficulties

    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
    iphate
    -0.74
    alian
    -0.71
    oleon
    -0.68
    minist
    -0.67
    agine
    -0.67
    uality
    -0.66
    obile
    -0.65
    ulhu
    -0.65
     Omn
    -0.64
    pires
    -0.64
    POSITIVE LOGITS
    neck
    1.13
     edges
    1.08
    housing
    0.98
    ness
    0.90
     approximation
    0.84
    cut
    0.81
     patches
    0.80
     rough
    0.77
     corners
    0.76
     terrain
    0.76
    Activations Density 0.030%

    No Known Activations