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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. 11-RES-JB
    6. 2913
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    INDEX
    Explanations

    actions or instructions related to cooking or preparing food

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating location or inclusion within a context

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    iffs
    -0.63
    rn
    -0.62
    Lew
    -0.58
    fn
    -0.58
    374
    -0.56
     defect
    -0.56
    iae
    -0.56
    itton
    -0.53
     Benn
    -0.53
    orem
    -0.52
    POSITIVE LOGITS
     fridge
    1.08
     blender
    1.07
     salads
    1.07
     bowls
    1.05
     jars
    1.02
    redients
    1.02
     refrigerator
    1.02
     batches
    0.96
     microwave
    0.95
     boiling
    0.93
    Activations Density 0.097%

    No Known Activations