readme: ---
  language:
  - en
  license: apache-2.0
  ---
  
  # mFLAG
  mFLAG is a sequence-to-sequence model for multi-figurative language generation. It was introduced in the paper [Multi-Figurative Language Generation](https://arxiv.org/abs/2209.01835) paper by [Huiyuan Lai](https://laihuiyuan.github.io/) and [Malvina Nissim](https://scholar.google.nl/citations?user=hnTpEOAAAAAJ&hl=en).
  
  # Model description
  mFLAG is a sequence-to-sequence model for multi-figurative language generation. It is trained by employing a scheme for multi-figurative language pre-training on top of BART, and a mechanism for injecting the target figurative information into the encoder; this enables the generation of text with the target figurative form from another figurative form without parallel figurative-figurative sentence pairs.
  
  
  # How to use
  ```bash
  git clone git@github.com:laihuiyuan/mFLAG.git
  cd mFLAG
  ```
  
  ```python
  from model import MultiFigurativeGeneration
  from tokenization_mflag import MFlagTokenizerFast
  tokenizer = MFlagTokenizerFast.from_pretrained('laihuiyuan/mFLAG')
  model = MultiFigurativeGeneration.from_pretrained('laihuiyuan/mFLAG')
  
  # hyperbole to sarcasm
  inp_ids = tokenizer.encode("<hyperbole> I am not happy that he urged me to finish all the hardest tasks in the world", return_tensors="pt")
  fig_ids = tokenizer.encode("<sarcasm>", add_special_tokens=False, return_tensors="pt")
  outs = model.generate(input_ids=inp_ids[:, 1:], fig_ids=fig_ids, forced_bos_token_id=fig_ids.item(), num_beams=5, max_length=60,)
  text = tokenizer.decode(outs[0, 2:].tolist(), skip_special_tokens=True, clean_up_tokenization_spaces=False)
  ```
  
  # Citation Info
  ```BibTeX
  @inproceedings{lai-etal-2022-multi,
      title = "Multi-Figurative Language Generation",
      author = "Lai, Huiyuan and Nissim, Malvina",
      booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
      month = October,
      year = "2022",
      address = "Gyeongju, Republic of korea",
  }
  ```