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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. 9-RES-JB
    11. 9137
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    Explanations

    phrases related to specific events and activities, such as refueling, undergoing treatment, entering premises, and causing controversy

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to legal or criminal situations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    renheit
    -0.67
    eday
    -0.65
    Ó
    -0.65
    eware
    -0.63
    Leaks
    -0.63
    VL
    -0.61
    ãĥ¯ãĥ³
    -0.61
    ouri
    -0.60
    Tokens
    -0.59
    Vo
    -0.59
    POSITIVE LOGITS
     AFB
    0.61
     lvl
    0.58
     Belfast
    0.58
     airstrike
    0.57
    )?
    0.56
     runway
    0.55
     ledge
    0.54
     ):
    0.54
     waitress
    0.54
    ©¶æ
    0.54
    Activations Density 0.574%

    No Known Activations