Update README.md

README.md

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 ---
 license: mit
 ---
+# roberta-temporal-predictor
+A RoBERTa-base model that is fine-tuned on the [The New York Times Annotated Corpus](https://catalog.ldc.upenn.edu/LDC2008T19)
+to predict temporal precedence of two events. This is used as the ``temporality prediction'' component
+in our ROCK framework for reasoning about commonsense causality. See our [paper](https://arxiv.org/abs/2202.00436) for more details.
+
+# Usage
+
+For simplicity, we implement the following TempPredictor class. Example usage using the ``TempPredictor`` class:
+```python
+from transformers import (RobertaForMaskedLM, RobertaTokenizer)
+from src.temp_predictor import TempPredictor
+
+TORCH_DEV = "cuda:0" # change as needed
+
+tp_roberta_ft = src.TempPredictor(
+    model=RobertaForMaskedLM.from_pretrained("CogComp/roberta-temporal-predictor"),
+    tokenizer=RobertaTokenizer.from_pretrained("CogComp/roberta-temporal-predictor"),
+    device=TORCH_DEV
+)
+
+E1 = "The man turned on the faucet."
+E2 = "Water flows out."
+t12 = tp_roberta_ft(E1, E2, top_k=5)
+print(f"P('{E1}' before '{E2}'): {t12}")
+```
+
+# BibTeX entry and citation info
+
+```bib
+@misc{zhang2022causal,
+      title={Causal Inference Principles for Reasoning about Commonsense Causality}, 
+      author={Jiayao Zhang and Hongming Zhang and Dan Roth and Weijie J. Su},
+      year={2022},
+      eprint={2202.00436},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```