|
--- |
|
language: zh |
|
tags: |
|
- sentiment-analysis |
|
- pytorch |
|
widget: |
|
- text: "房间非常非常小,内窗,特别不透气,因为夜里走廊灯光是亮的,内窗对着走廊,窗帘又不能完全拉死,怎么都会有一道光射进来。" |
|
- text: "尽快有洗衣房就好了。" |
|
- text: "很好,干净整洁,交通方便。" |
|
- text: "干净整洁很好" |
|
--- |
|
|
|
# Note |
|
|
|
BERT based sentiment analysis, finetune based on https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment .The model trained on hotel human review chinese datasets. |
|
|
|
# Usage |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline |
|
|
|
MODEL = "tezign/Erlangshen-Sentiment-FineTune" |
|
|
|
tokenizer = AutoTokenizer.from_pretrained(MODEL) |
|
|
|
model = AutoModelForSequenceClassification.from_pretrained(MODEL, trust_remote_code=True) |
|
|
|
classifier = TextClassificationPipeline(model=model, tokenizer=tokenizer) |
|
|
|
result = classifier("很好,干净整洁,交通方便。") |
|
|
|
print(result) |
|
|
|
""" |
|
print result |
|
>> [{'label': 'Positive', 'score': 0.989660382270813}] |
|
""" |
|
``` |