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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 0-RES-JB
    6. 24547
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    Explanations

    phrases related to readings or interpretations of data

    oai_token-act-pair · gpt-3.5-turbo

    terms and phrases related to readings and observations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     grooming
    -0.70
     burying
    -0.69
     bully
    -0.69
    ijk
    -0.67
     vanity
    -0.67
     Gron
    -0.66
     McGr
    -0.66
     stamp
    -0.65
     butt
    -0.65
     camel
    -0.64
    POSITIVE LOGITS
     readings
    2.54
    heard
    2.07
    seen
    1.69
    song
    1.56
    saw
    1.29
     Gathering
    1.06
    orders
    0.99
    warning
    0.96
    adiq
    0.95
     screenings
    0.94
    Activations Density 0.045%

    No Known Activations