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--- |
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license: mit |
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library_name: fasttext |
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pipeline_tag: text-classification |
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tags: |
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- pretraining-data-selection |
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--- |
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This fastText model is a filter for selecting high-quality pretraining data, as described in [Improving Pretraining Data Using Perplexity Correlations](https://arxiv.org/abs/2409.05816). It targets the LAMBADA IT task. |
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The model uses perplexity correlations to identify text segments highly correlated with strong performance on downstream benchmarks. It doesn't perform text classification directly; instead, it outputs a score indicating the suitability of a text segment for pretraining. |
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For complete usage instructions and the theoretical background, please refer to the [project's GitHub repository](https://github.com/TristanThrush/perplexity-correlations). |
