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---
language: en
widget:
- text: a 1968 american independent horror film \\n What is Night of the Living Dead?
---
# QA2Claim Model From ZeroFEC
ZeroFEC is a faithful and interpetable factual error correction framework introduced in the paper [Zero-shot Faithful Factual Error Correction](https://aclanthology.org/2023.acl-long.311/). It involves a component that converts qa-pairs to declarative statements, which is hosted in this repo. The associated code is released in [this](https://github.com/khuangaf/ZeroFEC) repository.
### How to use
Using Huggingface pipeline abstraction:
```python
from transformers import pipeline
nlp = pipeline("text2text-generation", model='khhuang/zerofec-qa2claim-t5-base', tokenizer='khhuang/zerofec-qa2claim-t5-base')
QUESTION = "What is Night of the Living Dead?"
ANSWER = "a 1968 american independent horror film"
def format_inputs(question: str, answer: str):
return f"{answer} \\n {question}"
text = format_inputs(QUESTION, ANSWER)
nlp(text)
# should output [{'generated_text': 'Night of the Living Dead is a 1968 american independent horror film.'}]
```
Using the pre-trained model directly:
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained('khhuang/zerofec-qa2claim-t5-base')
model = AutoModelForSeq2SeqLM.from_pretrained('khhuang/zerofec-qa2claim-t5-base')
QUESTION = "What is Night of the Living Dead?"
ANSWER = "a 1968 american independent horror film"
def format_inputs(question: str, answer: str):
return f"{answer} \\n {question}"
text = format_inputs(QUESTION, ANSWER)
input_ids = tokenizer(text, return_tensors="pt").input_ids
generated_ids = model.generate(input_ids, max_length=32, num_beams=4)
output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
print(output)
# should output "Night of the Living Dead is a 1968 american independent horror film."
```
### Citation
```
@inproceedings{huang-etal-2023-zero,
title = "Zero-shot Faithful Factual Error Correction",
author = "Huang, Kung-Hsiang and
Chan, Hou Pong and
Ji, Heng",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.311",
doi = "10.18653/v1/2023.acl-long.311",
pages = "5660--5676",
}
```