---
license: mit
language:
- en
pipeline_tag: text-classification
tags:
- code
---

# Emotion classification from 20 classes

## 20 Emotion labels
| id  | label      |
| --- | ---------- |
| 0   | anger      |
| 1   | cheeky     |
| 2   | confuse    |
| 3   | curious    |
| 4   | disgust    |
| 5   | empathetic |
| 6   | energetic  |
| 7   | fear       |
| 8   | grumpy     |
| 9   | guilty     |
| 10  | impatient  |
| 11  | joy        |
| 12  | love       |
| 13  | neutral    |
| 14  | sadness    |
| 15  | serious    |
| 16  | surprise   |
| 17  | suspicious |
| 18  | think      |
| 19  | whiny      |


## How to use
Here is how to use this model to get the emotion label of a given text:


```python
from transformers import AutoModelForSequenceClassification, pipeline

model_name = 'jitesh/emotion-english'
model = AutoModelForSequenceClassification.from_pretrained(model_name)
classifier = pipeline("text-classification", model=model, tokenizer=model_name)

text = "I can't wait any longer "

prediction = classifier(text)
print(prediction[0], text)
```

The above code outputs the following line.
```bash
{'label': 'impatient', 'score': 0.924211859703064} I can't wait any longer 
```