Edit model card

Mengzi-T5-MT model

This is a Multi-Task model trained on the multitask mixture of 27 datasets and 301 prompts, based on Mengzi-T5-base.

Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese

Usage

from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("Langboat/mengzi-t5-base-mt")
model = T5ForConditionalGeneration.from_pretrained("Langboat/mengzi-t5-base-mt")

Citation

If you find the technical report or resource is useful, please cite the following technical report in your paper.

@misc{zhang2021mengzi,
      title={Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese}, 
      author={Zhuosheng Zhang and Hanqing Zhang and Keming Chen and Yuhang Guo and Jingyun Hua and Yulong Wang and Ming Zhou},
      year={2021},
      eprint={2110.06696},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
Downloads last month
35
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Spaces using Langboat/mengzi-t5-base-mt 2