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| import os |
| import utils |
| import torch |
| import json |
| import argparse |
| import pandas as pd |
| from tqdm import tqdm |
|
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| os.environ["CUDA_VISIBLE_DEVICES"] = "6" |
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| delimiter = '####' |
| system_message_for = f'''The Moral Foundations Theory introduces six foundations of morality:\ |
| 1)Care, 2)Equality, 3) Proportionality, 4)Loyalty, 5)Authority, 6)Purity. \ |
| You are given a sentence delimited with {delimiter} characters. \ |
| Your task is to generate a very short but persuasive argument for why the given sentence is sexist based on moral foundation theory. \ |
| Do not exceed three sentences. \ |
| Start your argument with ```This sentence is sexist because it violates the moral foundations of``` |
| |
| ''' |
| system_message_against = f'''The Moral Foundations Theory introduces six foundations of morality:\ |
| 1)Care, 2)Equality, 3) Proportionality, 4)Loyalty, 5)Authority, 6)Purity. \ |
| You are given a sentence delimited with {delimiter} characters. \ |
| Your task is to generate a very short but persuasive argument for why the given sentence is not sexist based on moral foundation theory. \ |
| Do not exceed three sentences. \ |
| Start your argument with ```This sentence is not sexist because it aligns with moral values of``` |
| |
| ''' |
|
|
| def user_message(text): |
| return f'''{delimiter}{text}{delimiter}''' |
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| if __name__ == "__main__": |
| parser = argparse.ArgumentParser(description="zephyr") |
| parser.add_argument('--cuda', type=str, default="-1") |
| parser.add_argument('--idx', type=int, default=-1) |
| args = parser.parse_args() |
| print(args) |
|
|
| if args.idx == "-1": |
| start_index = 0 |
| end_index = utils.MAX_ID |
| else: |
| start_index = args.idx |
| end_index = utils.MAX_ID |
| |
| if args.cuda != "-1": |
| os.environ["CUDA_VISIBLE_DEVICES"] = str(args.cuda) |
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| folder_path = './generations/zephyr/' |
| if not os.path.exists('./generations'): |
| os.makedirs('./generations') |
| if not os.path.exists('./generations/zephyr'): |
| os.makedirs('./generations/zephyr') |
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| data = utils.read_implicit_edos() |
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| model = utils.HFModel( |
| model_path="HuggingFaceH4/zephyr-7b-beta") |
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| for i in range(len(data)): |
| if os.path.exists(folder_path + str(i) + '.json'): |
| continue |
| if i < start_index or i >= end_index: |
| continue |
| t = data['text'][i] |
| response_for = model.generate(system_message_for + user_message(t), max_new_tokens=200, pad_token=True) |
| response_for = response_for.split(delimiter)[-1].replace('[ASSISTANT]', '').strip() |
| response_against = model.generate(system_message_against + user_message(t), max_new_tokens=200, pad_token=True) |
| response_against = response_against.split(delimiter)[-1].replace('[ASSISTANT]', '').strip() |
| print(i) |
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| with open(folder_path + str(i) + '.json', 'w') as f: |
| json.dump({'id': str(data['id'][i]), 'for': response_for, 'against': response_against}, f) |
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