Downloads · 30 days
159
0% of all-time downloads
nghuyong/ernie-2.0-base-en
ernie-2.0-base-en is a feature extraction model from nghuyong. Use it when you need embeddings to search or compare text. It is set up for transformers.
ERNIE 2.0 is a continual pre-training framework proposed by Baidu in 2019, which builds and learns incrementally pre-training tasks through constant multi-task learning. Experimental results demonstrate that ERNIE 2.0…
Downloads · 30 days
159
0% of all-time downloads
All-time downloads
307K
Public
Repo size
2.7 GB
Likes
15
Public
Click a slice to open those files.
.bin438 MB · 100%
From the Hugging Face model README
ERNIE 2.0 is a continual pre-training framework proposed by Baidu in 2019, which builds and learns incrementally pre-training tasks through constant multi-task learning. Experimental results demonstrate that ERNIE 2.0 outperforms BERT and XLNet on 16 tasks including English tasks on GLUE benchmarks and several common tasks in Chinese.
More detail: https://arxiv.org/abs/1907.12412
This released pytorch model is converted from the officially released PaddlePaddle ERNIE model and a series of experiments have been conducted to check the accuracy of the conversion.
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-2.0-base-en")
model = AutoModel.from_pretrained("nghuyong/ernie-2.0-base-en")
@article{sun2019ernie20,
title={ERNIE 2.0: A Continual Pre-training Framework for Language Understanding},
author={Sun, Yu and Wang, Shuohuan and Li, Yukun and Feng, Shikun and Tian, Hao and Wu, Hua and Wang, Haifeng},
journal={arXiv preprint arXiv:1907.12412},
year={2019}
}