# abductive-commonsense-reasoning **Repository Path**: wandehua/abductive-commonsense-reasoning ## Basic Information - **Project Name**: abductive-commonsense-reasoning - **Description**: 常识溯因推理Abductive Reasoning - **Primary Language**: Python - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-10-15 - **Last Updated**: 2022-05-25 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # abductive-commonsense-reasoning Public repository associated with [Abductive Commonsense Reasoning, ICLR 2020](https://arxiv.org/abs/1908.05739) # Setup 1. Clone the repo ``` git clone git@github.com:allenai/abductive-commonsense-reasoning.git ``` 2. Install requirements in a Python 3.7 environment ``` pip install -r requirements.txt ``` 3. Download Data and Models ``` sh get-data.sh ``` The script will create `data/` and `models/` directories containing subdirectories `anli` and `anlg` for the Abuctive Inference and Generation tasks respectively. The size of the data and models is around *12G*. If you'd like to download data: wget https://storage.googleapis.com/ai2-mosaic/public/abductive-commonsense-reasoning-iclr2020/anli.zip wget https://storage.googleapis.com/ai2-mosaic/public/abductive-commonsense-reasoning-iclr2020/anlg.zip # Tasks 1. [Abductive Inference](anli/README.md) ### Interactive Demo ``` python anli/demo.py --saved_model_dir models/bert-ft-lr1e-5-batch8-epoch4/ --gpu_id 0 --interactive ``` 2. [Abductive Generation](anlg/README.md) # References ``` @inproceedings{ bhagavatula2020abductive, title={Abductive Commonsense Reasoning}, author={Chandra Bhagavatula and Ronan Le Bras and Chaitanya Malaviya and Keisuke Sakaguchi and Ari Holtzman and Hannah Rashkin and Doug Downey and Wen-tau Yih and Yejin Choi}, booktitle={International Conference on Learning Representations}, year={2020}, url={https://openreview.net/forum?id=Byg1v1HKDB} } ```