tweet_generation / process /tweet_qa.py
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import os
import json
from datasets import load_dataset
data = load_dataset("lmqg/qg_tweetqa")
def process(tmp):
tmp = [i.to_dict() for _, i in tmp.iterrows()]
for i in tmp:
i.pop('paragraph_question')
i.pop('question')
i['text'] = i.pop("paragraph")
i['condition'] = f'Keyword: {i.pop("answer")}'
tmp = [i for i in tmp if 'http' not in i['text']]
return tmp
train = process(data["train"].to_pandas())
val = process(data["validation"].to_pandas())
test = process(data["test"].to_pandas())
os.makedirs("dataset/qa", exist_ok=True)
with open("dataset/qa/train.jsonl", "w") as f:
f.write("\n".join([json.dumps(i) for i in train]))
with open("dataset/qa/validation.jsonl", "w") as f:
f.write("\n".join([json.dumps(i) for i in val]))
with open("dataset/qa/test.jsonl", "w") as f:
f.write("\n".join([json.dumps(i) for i in test]))