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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. 24250
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    Explanations

    specific information, such as names, descriptions, and terms

    oai_token-act-pair · gpt-3.5-turbo

    elements related to details and logistics in a process or plan

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    ĸļ
    -0.80
     Shutterstock
    -0.74
    ²
    -0.64
    Ħ¢
    -0.64
    entimes
    -0.62
    riot
    -0.62
     Byrne
    -0.62
    ©¶æ¥µ
    -0.62
    umblr
    -0.61
    Ŀ
    -0.61
    POSITIVE LOGITS
     accordingly
    1.00
     beforehand
    0.95
     parameters
    0.89
     exactly
    0.84
     probabilities
    0.84
     requirements
    0.82
    liest
    0.82
     thresholds
    0.81
     optimal
    0.81
     ranges
    0.81
    Activations Density 0.496%

    No Known Activations