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Update README.txt (#8957)

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Nguyen Van Nha 2020-12-08 04:01:49 +07:00 committed by GitHub
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model_cards/NlpHUST/vibert4news-base-cased/README.md
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@ -1,7 +1,6 @@
---
language: vn
---
# BERT for Vietnamese is trained on more 20 GB news dataset
Apply for task sentiment analysis on using [AIViVN's comments dataset](https://www.aivivn.com/contests/6)
@ -19,7 +18,24 @@ You can download trained model:
- [tensorflow](https://drive.google.com/file/d/1X-sRDYf7moS_h61J3L79NkMVGHP-P-k5/view?usp=sharing).
- [pytorch](https://drive.google.com/file/d/11aFSTpYIurn-oI2XpAmcCTccB_AonMOu/view?usp=sharing).
Use with huggingface/transformers
``` bash
import torch
from transformers import AutoTokenizer,AutoModel
tokenizer= AutoTokenizer.from_pretrained("NlpHUST/vibert4news-base-cased")
bert_model = AutoModel.from_pretrained("NlpHUST/vibert4news-base-cased")
line = "Tôi là sinh viên trường Bách Khoa Hà Nội ."
input_id = tokenizer.encode(line,add_special_tokens = True)
att_mask = [int(token_id > 0) for token_id in input_id]
input_ids = torch.tensor([input_id])
att_masks = torch.tensor([att_mask])
with torch.no_grad():
features = bert_model(input_ids,att_masks)
print(features)
```
Run training with base config
@ -36,3 +52,4 @@ python train_pytorch.py \
### Contact information
For personal communication related to this project, please contact Nha Nguyen Van (nha282@gmail.com).