Text2Text Generation
Transformers
PyTorch
bart
feature-extraction
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  ---
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  datasets:
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  - yuvalkirstain/summ_screen_fd_t5_lm
 
 
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  pipeline_tag: text2text-generation
 
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  ---
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  Model from the preprint [Unlimiformer: Long-Range Transformers with Unlimited Length Input](https://arxiv.org/abs/2305.01625).
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  This model was finetuned from a BART-base model using the retrieval-augmented training strategy described in section 3.2 of the paper. It was finetuned on the dataset SummScreen using the data preprocessing pipeline from SLED; to load the validation or test set for use with these model, please use the datasets [urialon/summ_screen_validation](https://huggingface.co/datasets/urialon/summ_screen_validation) and [urialon/summ_screen_test](https://huggingface.co/datasets/urialon/summ_screen_test).
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- This is the strongest of the Unlimiformer models for SummScreen.
 
 
 
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  datasets:
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  - yuvalkirstain/summ_screen_fd_t5_lm
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+ - urialon/summ_screen_validation
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+ - urialon/summ_screen_test
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  pipeline_tag: text2text-generation
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+ inference: false
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  ---
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  Model from the preprint [Unlimiformer: Long-Range Transformers with Unlimited Length Input](https://arxiv.org/abs/2305.01625).
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  This model was finetuned from a BART-base model using the retrieval-augmented training strategy described in section 3.2 of the paper. It was finetuned on the dataset SummScreen using the data preprocessing pipeline from SLED; to load the validation or test set for use with these model, please use the datasets [urialon/summ_screen_validation](https://huggingface.co/datasets/urialon/summ_screen_validation) and [urialon/summ_screen_test](https://huggingface.co/datasets/urialon/summ_screen_test).
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+ This is the strongest of the Unlimiformer models for SummScreen.
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+ *The inference demo is disabled because you must add the Unlimiformer files to your repo before this model can handle unlimited length input!* See the [Unlimiformer GitHub](https://github.com/abertsch72/unlimiformer) for setup instructions.