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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. 2-RES-JB
    6. 8320
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    Explanations

    phrases indicating someone being caught in a negative or suspicious situation

    oai_token-act-pair · gpt-3.5-turbo
    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
     pronoun
    -0.74
    eth
    -0.74
     pronouns
    -0.71
    ciplinary
    -0.70
     helicop
    -0.70
    htar
    -0.70
    xual
    -0.68
    umably
    -0.68
    estate
    -0.66
    ensible
    -0.66
    POSITIVE LOGITS
    ãĤµ
    0.85
    ãĤ¤
    0.76
     Tracks
    0.74
     Luffy
    0.74
     Rai
    0.73
    ãĥĩãĤ£
    0.72
    ãĤ¤ãĥĪ
    0.72
     caught
    0.72
    ãĥĥãĥī
    0.71
    Frames
    0.70
    Activations Density 0.012%

    No Known Activations