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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. 6-RES-JB
    11. 4359
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    Explanations

    various types of cheese

    oai_token-act-pair · gpt-3.5-turbo

    different types of cheese

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    nant
    -0.76
    igious
    -0.76
    oday
    -0.74
     glim
    -0.73
    aylor
    -0.67
    rians
    -0.67
    nce
    -0.66
    ounces
    -0.66
    uating
    -0.66
    ITNESS
    -0.66
    POSITIVE LOGITS
    cloth
    1.29
     slic
    0.93
    ecake
    0.93
     cheese
    0.89
    mint
    0.84
    weed
    0.83
    bowl
    0.83
    fruit
    0.83
     sandwich
    0.81
     lick
    0.80
    Activations Density 0.015%

    No Known Activations