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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. 3-RES-JB
    6. 1220
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    INDEX
    Explanations

    the word "bad" with varying levels of intensity

    oai_token-act-pair · gpt-3.5-turbo

    expressions related to negative evaluations or criticisms

    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
    ĸļ
    -0.91
    eters
    -0.84
    arov
    -0.82
    ittees
    -0.76
    ittee
    -0.76
    ando
    -0.74
    olate
    -0.74
    ipel
    -0.74
    gow
    -0.73
    ktop
    -0.73
    POSITIVE LOGITS
    dest
    1.00
    dies
    0.91
     karma
    0.86
    die
    0.84
    enough
    0.82
     vib
    0.81
     luck
    0.81
     adolesc
    0.79
     manners
    0.77
     enough
    0.76
    Activations Density 0.022%

    No Known Activations