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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. 5-RES-JB
    6. 4986
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    Explanations

    words related to negative actions or characteristics, such as hate, murder, and suspicion

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "sn" or variations of it, likely indicating a focus on snarky or sarcastic commentary

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    heid
    -0.87
    EMENT
    -0.76
    xual
    -0.72
    WAYS
    -0.64
    mine
    -0.63
     PowerPoint
    -0.62
    minus
    -0.61
    shire
    -0.60
    geist
    -0.60
     Sacrament
    -0.59
    POSITIVE LOGITS
    atching
    1.19
    obb
    1.15
    atches
    1.13
    agged
    1.12
    agging
    1.11
    appers
    1.09
    appy
    1.08
    apper
    1.08
    apping
    1.07
    ugg
    1.06
    Activations Density 0.009%

    No Known Activations