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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 6-RES-JB
    6. 6760
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    Explanations

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    oai_token-act-pair · gpt-3.5-turbo

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    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
     duplication
    -0.64
     decomp
    -0.63
     recording
    -0.60
     gib
    -0.58
     fragmentation
    -0.57
     recovery
    -0.55
     unmarked
    -0.55
     stabilization
    -0.55
     GPS
    -0.54
     forwarded
    -0.54
    POSITIVE LOGITS
    £
    1.04
    Ĵ
    0.94
    ¬
    0.93
    Ń
    0.93
    º
    0.90
    ķ
    0.88
    ¾
    0.87
    ¹
    0.86
    ı
    0.85
    ½
    0.83
    Activations Density 0.546%

    No Known Activations