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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. 10-RES-JB
    6. 7911
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    Explanations

    phrases related to significant impacts or surprises

    oai_token-act-pair · gpt-3.5-turbo

    expressions related to overwhelming impact or intensity

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    enhagen
    -0.88
    cliffe
    -0.86
    arten
    -0.76
    aepernick
    -0.74
    orea
    -0.73
    oran
    -0.72
    ulia
    -0.69
    leness
    -0.68
    vec
    -0.67
    ngth
    -0.67
    POSITIVE LOGITS
     fuse
    0.99
     socks
    0.92
     whistle
    0.89
     lid
    0.89
     crap
    0.84
     tires
    0.83
    shit
    0.83
     horn
    0.82
     tyres
    0.80
     itch
    0.80
    Activations Density 0.111%

    No Known Activations