Downloads · 30 days
14
12% of all-time downloads
KNNFx/mt5-mcqa-history-no-explain
mt5-mcqa-history-no-explain is a question answering model from KNNFx. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.
This model is a fine-tuned version of csebuetnlp/mT5multilingualXLSum specifically trained for Vietnamese history multiple choice question answering tasks. The model is designed to answer historical questions without…
Downloads · 30 days
14
12% of all-time downloads
All-time downloads
113
Public
Parameters
582M
2.4 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors2.3 GB · 99%
From the Hugging Face model README
This model is a fine-tuned version of csebuetnlp/mT5_multilingual_XLSum specifically trained for Vietnamese history multiple choice question answering tasks. The model is designed to answer historical questions without providing explanations.
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("KNNFx/mt5-mcqa-history-no-explain")
model = AutoModelForSeq2SeqLM.from_pretrained("KNNFx/mt5-mcqa-history-no-explain")
# Example usage
question = "Ai là vua đầu tiên của nhà Nguyễn?"
choices = ["A. Nguyễn Ánh", "B. Gia Long", "C. Minh Mạng", "D. Thiệu Trị"]
input_text = f"Question: {question} Choices: {', '.join(choices)}"
inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
outputs = model.generate(**inputs, max_length=10)
answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
The model was trained on Vietnamese history questions covering various periods and topics in Vietnamese history.
This model focuses on accuracy without explanation generation, making it suitable for applications requiring quick and direct answers to historical questions.
If you use this model in your research, please cite:
@misc{mt5-mcqa-history-no-explain,
title={mT5 Multiple Choice QA Model for Vietnamese History},
author={KNNFx},
year={2025},
url={https://huggingface.co/KNNFx/mt5-mcqa-history-no-explain}
}
This model is released under the MIT License.