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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. 2-RES-JB
    11. 5363
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    INDEX
    Explanations

    positive adjectives describing high quality

    oai_token-act-pair · gpt-3.5-turbo

    high ratings or evaluations of quality

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ople
    -0.82
    ften
    -0.76
    vere
    -0.75
    NetMessage
    -0.72
    pai
    -0.72
    psy
    -0.70
    pper
    -0.70
    soDeliveryDate
    -0.69
    MG
    -0.68
    Hop
    -0.67
    POSITIVE LOGITS
     quality
    0.95
     enough
    0.82
     teamwork
    0.80
     opportunity
    0.76
    NESS
    0.76
     specimen
    0.76
     preservation
    0.75
     prospects
    0.74
     introductory
    0.74
    enough
    0.73
    Activations Density 0.021%

    No Known Activations