## swtx SIMCSE RoBERTa WWM Ext Chinese

This model provides simplified Chinese sentence embeddings encoding based on [Simple Contrastive Learning](https://arxiv.org/abs/2104.08821).
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding.

	
## How to use
```Python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("swtx/simcse-chinese-roberta-wwm-ext")
model = AutoModel.from_pretrained("swtx/simcse-chinese-roberta-wwm-ext")
```
{}
transformers pytorch bert feature-extraction arxiv:2104.08821 endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2104.08821 #endpoints_compatible #region-us 

## swtx SIMCSE RoBERTa WWM Ext Chinese

This model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding.

	
## How to use

## swtx SIMCSE RoBERTa WWM Ext Chinese

This model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding. ## How to use
TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2104.08821 #endpoints_compatible #region-us 
 ## swtx SIMCSE RoBERTa WWM Ext Chinese

This model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding. ## How to use
passage: TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2104.08821 #endpoints_compatible #region-us 
## swtx SIMCSE RoBERTa WWM Ext Chinese

This model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding.## How to use