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This is [DeBERTa-v3-base](https://hf.co/microsoft/deberta-v3-base) fine-tuned with multi-task learning on 600 tasks of the [tasksource collection](https://github.com/sileod/tasksource/).
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This checkpoint has strong zero-shot validation performance on many tasks (e.g. 70% on WNLI), and can be used for:
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- Zero-shot entailment-based classification pipeline (similar to bart-mnli)
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- Natural language inference [NLI]
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- Hundreds of other tasks with tasksource-adapters
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- Further fine-tuning with a new task or tasksource task (classification, token classification or multiple-choice) [FT].
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# [ZS] Zero-shot classification pipeline
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This is [DeBERTa-v3-base](https://hf.co/microsoft/deberta-v3-base) fine-tuned with multi-task learning on 600 tasks of the [tasksource collection](https://github.com/sileod/tasksource/).
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This checkpoint has strong zero-shot validation performance on many tasks (e.g. 70% on WNLI), and can be used for:
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- Zero-shot entailment-based classification pipeline (similar to bart-mnli) [ZS].
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- Natural language inference [NLI]
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- Hundreds of other tasks with tasksource-adapters [TA].
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- Further fine-tuning with a new task or tasksource task (classification, token classification or multiple-choice) [FT].
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# [ZS] Zero-shot classification pipeline
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