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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. 2-RES-JB
    11. 18376
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    Explanations

    names, particularly those with variations like "Ri" and "Hau", often repeated in different contexts

    oai_token-act-pair · gpt-3.5-turbo

    proper nouns, particularly names of individuals or entities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    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
    ments
    -0.91
    matic
    -0.81
    mentation
    -0.79
    "]=>
    -0.77
     Pompe
    -0.77
    ment
    -0.76
    graduate
    -0.76
    erous
    -0.75
     Dragonbound
    -0.73
     Izan
    -0.71
    POSITIVE LOGITS
    senal
    1.00
     Ri
    0.95
    emer
    0.93
    okin
    0.87
    quet
    0.81
    ordan
    0.79
    isine
    0.78
    omon
    0.77
    uth
    0.76
    assic
    0.76
    Activations Density 0.009%

    No Known Activations