Update README.md

README.md

@@ -1,3 +1,57 @@
 ---
 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 
+```