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README.md

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1. Cache activations for the first 10 million tokens of EleutherAI/rpj-v2-sample.
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2. Generate explanations for the first 100 features of layer 5 using the specified explainer model.
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3. Score the explanations uses fuzzing and detection scorers.
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4. Log summary metrics including per-scorer F1 scores and confusion matrices.
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4. Log summary metrics including per-scorer F1 scores and confusion matrices, and produce histograms of the scorer classification accuracies.
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The pipeline is highly configurable and can also be called programmatically (see the [end-to-end test](https://github.com/EleutherAI/delphi/blob/main/delphi/tests/e2e.py) for an example).
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