AFFGEN

Code implementation for EMNLP-findings 2023 paper "Affective and Dynamic Beam Search for Story Generation"

Requirements

Before you begin, ensure you have met the following requirements:

• Python 3.6 or later
• Pip for installing Python packages
• Access to command-line interface or terminal

Setup Instructions

Follow these steps to get your environment ready:

1. Clone the Repository

2. Install Dependencies

   pip install -r requirements.txt
   

3. Download Required Models and Datasets

   • ROCStories Dataset: Download the dataset from https://cs.rochester.edu/nlp/rocstories/ and save it to story_path.

   • GPT-2 Model: Download GPT-2-large from Huggingface and finetune it on ROCStories. Save the finetuned model to GPT2_finetuned_ROC.

   • Roberta Model: Download Roberta from Huggingface and train it with the dataset from https://github.com/dbamman/litbank for identifying literary event triggers. The model should be saved to event_trigger_path. We will release the train script for event trigger soon.

   • NRC Emotion Lexicon: Download from https://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm and save the lexicon to NRC_lexicon_path.

4. Configuration

   Update the Config class in your project with the paths to the downloaded models and datasets. Here is an example of what the Config class.

5. Running the Project

   After setting up the configuration, you can run your project by executing the main script. Adjust the command based on your project's structure.

   python inference.py
   

The bandit framework is adapted from contextual-bandit.