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WQ data for deberta-v2-xlarge-mnlithis data is already under the releases for tag v0.1.1 but putting it here too: summary_gauntlet_dataset_mapped_src_docs_WQ_predictionsdeberta-v2-xlarge-mnli.csv summary_gauntlet_dataset_mapped_src_docs_WQ_predictionsdeberta-v2-xlarge-mnli.zip |
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token lengths
Name: summary_tokens_long-t5-tglobal-base, dtype: float64
Name: summary_tokens_pythia-2.8b, dtype: float64
Name: summary_tokens_deberta-large-mnli, dtype: float64
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initial data trends and analysis
this is a discussion to post/discuss etc about trends/analysis for the initial version (release
v0.1.1
):example topics
Some initial ideas of things to explore, discuss, and investigate:
Writing Quality - some details
Some additional details/exports:
microsoft/deberta-v2-xlarge-mnli
running zero-shot writing quality inferenceBeta Was this translation helpful? Give feedback.
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