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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. 24550
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    INDEX
    Explanations

    phrases related to important, debated or significant matters or decisions

    oai_token-act-pair · gpt-3.5-turbo

    key matters and significant elements in discussions

    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
    vez
    -0.81
    ateurs
    -0.81
    ammers
    -0.80
    osponsors
    -0.77
     flats
    -0.76
    visors
    -0.72
    ooks
    -0.72
    ippers
    -0.71
    undai
    -0.71
    viks
    -0.71
    POSITIVE LOGITS
     imaginable
    1.01
     involving
    0.87
    =/
    0.79
    ="/
    0.79
    phrase
    0.76
     namely
    0.69
     called
    0.69
     ("
    0.69
     relating
    0.68
     spree
    0.68
    Activations Density 0.502%

    No Known Activations