Text2Text Generation
Transformers
PyTorch
bart
feature-extraction
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---
datasets:
- yuvalkirstain/summ_screen_fd_t5_lm
- urialon/summ_screen_validation
- urialon/summ_screen_test
inference: false
pipeline_tag: text2text-generation
---

Model from the preprint [Unlimiformer: Long-Range Transformers with Unlimited Length Input](https://arxiv.org/abs/2305.01625).

This model was finetuned from a BART-base model using Unlimiformer-aware early stopping, described in section 3.1 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).

This is generally a weaker model than the [retrieval-trained model](https://huggingface.co/abertsch/unlimiformer-bart-summscreen-retrieval) and a stronger model than the [baseline](https://huggingface.co/abertsch/bart-base-summscreen).

*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.