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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. 3-RES-JB
    11. 12439
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    Explanations

    phrases related to environmental impact from human activities, particularly logging and habitat destruction

    oai_token-act-pair · gpt-3.5-turbo

    terms related to environmental impact and conservation issues

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    £ı
    -0.95
    FY
    -0.77
    soft
    -0.76
    ĸļ
    -0.76
    rawdownloadcloneembedreportprint
    -0.75
    EStream
    -0.74
    ulz
    -0.73
    Merit
    -0.73
     Cyber
    -0.73
    ONY
    -0.72
    POSITIVE LOGITS
     farms
    0.97
     dams
    0.93
     herds
    0.87
     habitats
    0.86
     fisheries
    0.86
     fishermen
    0.85
     ponds
    0.84
     biodiversity
    0.83
     harvesting
    0.83
     fisher
    0.82
    Activations Density 0.415%

    No Known Activations