language: en | |
tags: | |
- text-classification | |
- tensorflow | |
- roberta | |
datasets: | |
- go_emotions | |
license: mit | |
## What is the GoEmotions Dataset? | |
The dataset is comprised of 58000 Reddit comments with 28 emotions. | |
- admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise | |
## Usage | |
```python | |
from transformers import RobertaTokenizerFast, TFRobertaForSequenceClassification, pipeline | |
tokenizer = RobertaTokenizerFast.from_pretrained("cappuch/EmoRoBERTa_Retrain") | |
model = TFRobertaForSequenceClassification.from_pretrained("cappuch/EmoRoBERTa_Retrain") | |
emotion = pipeline('sentiment-analysis', | |
model='cappuch/EmoRoBERTa_Retrain') | |
emotion_labels = emotion("Hello!") | |
print(emotion_labels) | |
#[{'label': 'neutral', 'score': 0.9964383244514465}] | |
``` | |