
# ERNIE-Gram-chinese

## Introduction

ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding

More detail: https://arxiv.org/abs/2010.12148

## Released Model Info

|Model Name|Language|Model Structure|
|:---:|:---:|:---:|
|ernie-gram-chinese| Chinese |Layer:12, Hidden:768, Heads:12|

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.

- Official PaddlePaddle ERNIE repo: https://github.com/PaddlePaddle/ERNIE
- Pytorch Conversion repo:  https://github.com/nghuyong/ERNIE-Pytorch

## How to use
```Python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("swtx/ernie-gram-chinese")
model = AutoModel.from_pretrained("swtx/ernie-gram-chinese")
```
{"language": "chinese"}
transformers pytorch bert feature-extraction arxiv:2010.12148 endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2010.12148 #endpoints_compatible #region-us 

ERNIE-Gram-chinese
==================


Introduction
------------


ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding


More detail: URL


Released Model Info
-------------------



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.


* Official PaddlePaddle ERNIE repo: URL
* Pytorch Conversion repo: URL


How to use
----------



TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2010.12148 #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2010.12148 #endpoints_compatible #region-us 
