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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 7-RES-JB
    6. 3247
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    Explanations

    adjectives describing the degree or intensity of something

    oai_token-act-pair · gpt-3.5-turbo

    intensifiers or descriptors of extremity and severity

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ¶æ
    -0.66
    ãĥīãĥ©ãĤ´ãĥ³
    -0.65
    OPS
    -0.64
    ¦
    -0.64
    Ô
    -0.60
    ighth
    -0.60
    ¸
    -0.59
    Pope
    -0.59
     permitting
    -0.58
    zsche
    -0.58
    POSITIVE LOGITS
    enos
    0.81
    amus
    0.77
    ranged
    0.76
    ense
    0.74
    eous
    0.72
    ocating
    0.70
    yip
    0.70
    !!!!!!!!
    0.68
    ciating
    0.67
    lly
    0.65
    Activations Density 0.096%

    No Known Activations