---
datasets:
- abertsch/booksum-fullbooks
pipeline_tag: text2text-generation
inference: false
---
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 the random-encoding training strategy described in section 3.2 of the paper. It was finetuned on the dataset BookSum (full-book setting).

*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.