Create README.md

README.md

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+---
+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]() paper by Huiyuan Lai and Malvina Nissim.
+
+# 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('checkpoints/mFLAG')
+model = MultiFigurativeGeneration.from_pretrained('checkpoints/mFLAG')
+
+# hyperbole to sarcasm
+inp_id = tokenizer.encode("<hyperbole> I am not happy that he urged me to finish all the hardest tasks in the world", return_tensors="pt")
+fig_id = tokenizer.encode("<sarcasm>", add_special_tokens=False, return_tensors="pt")
+
+outs = model.generate(input_ids=inp_id[:, 1:], fig_ids=fig_id, forced_bos_token_id=fig_id.item())
+text = tokenizer.decode(outs[0].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",
+}
+```