
[**GitHub Homepage**](https://github.com/hunterdie333/Dazk-Nhan-Dien-Tot-Xau)


Labels:
- NEG: Tiêu cực
- POS: Tích cực
- NEU: Trung lập

Dataset: [Từ từ sẽ được update](https://www.kaggle.com/datasets/linhlpv/vietnamese-sentiment-analyst)

## Usage
```python
import torch
from transformers import RobertaForSequenceClassification, AutoTokenizer

model = RobertaForSequenceClassification.from_pretrained("hunterdie333/Dazk-Nhan-Dien-Tot-Xau")

tokenizer = AutoTokenizer.from_pretrained("hunterdie333/Dazk-Nhan-Dien-Tot-Xau", use_fast=False)

# Just like PhoBERT: INPUT TEXT MUST BE ALREADY WORD-SEGMENTED!
sentence = 'Mô hình được clone lại bởi DazkDev'  

input_ids = torch.tensor([tokenizer.encode(sentence)])

with torch.no_grad():
    out = model(input_ids)
    print(out.logits.softmax(dim=-1).tolist())
    # Output:
    # [[0.293, 0.040, 0.667]]
    #     ^      ^      ^
    #    NEG    POS    NEU
```
{"language": ["vi"], "license": "mit", "tags": ["sentiment", "classification"], "widget": [{"text": "M\u00f4 h\u00ecnh \u0111\u01b0\u1ee3c clone l\u1ea1i b\u1edfi DazkDev"}]}
transformers pytorch roberta text-classification sentiment classification vi license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #sentiment #classification #vi #license-mit #autotrain_compatible #endpoints_compatible #region-us 


GitHub Homepage


Labels:
- NEG: Tiêu cực
- POS: Tích cực
- NEU: Trung lập

Dataset: Từ từ sẽ được update

## Usage

## Usage
TAGS
#transformers #pytorch #roberta #text-classification #sentiment #classification #vi #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ## Usage