metadata

license: mit
language:
  - en
pipeline_tag: text-classification
tags:
  - emotion
  - 20 classes
  - code
  - emotions
widget:
  - text: I'm so angry right now. I can't believe he did that to me.
    example_title: anger
  - text: I'm feeling disgusted by the smell of this food.
    example_title: disgust
  - text: I'm feeling very afraid of what might happen next.
    example_title: fear
  - text: I'm so joyful right now! This is the best day of my life.
    example_title: joy
  - text: >-
      I'm feeling neutral about this situation. I don't really care one way or
      another.
    example_title: neutral
  - text: I'm feeling really sad today after my dog passed away."
    example_title: sadness
  - text: I'm so surprised by what just happened! I never saw that coming.
    example_title: surprise
  - text: I'm feeling cheeky today. I'm going to play a little prank on my friend.
    example_title: cheeky
  - text: I'm feeling confused about what to do next. I need some guidance.
    example_title: confuse
  - text: I'm feeling curious about the world around me. There's so much to learn!
    example_title: curious
  - text: >-
      I'm feeling empathetic towards my friend who is going through a tough
      time.
    example_title: empathetic
  - text: I'm feeling grumpy today. Everything is annoying me!
    example_title: grumpy
  - text: I'm feeling guilty about what I did. I wish I could take it back.
    example_title: guilty
  - text: I'm feeling very energetic today. I'm ready to take on the world!
    example_title: energetic
  - text: I'm feeling impatient waiting for this movie to start.
    example_title: impatient
  - text: >-
      I'm feeling so much love for my family right now. They mean everything to
      me.
    example_title: love
  - text: I'm thinking about my future and what I want to achieve.
    example_title: think
  - text: >-
      I'm feeling serious about this issue. It's important and needs to be
      addressed.
    example_title: serious
  - text: >-
      I'm feeling suspicious of what he's telling me. I think he's hiding
      something.
    example_title: suspicious
  - text: I'm feeling whiny today. Everything is bothering me!
    example_title: whiny
  - text: I love football so much
    example_title: love 2
  - text: I'm reflecting on my experiences to gain insights
    example_title: think 2
  - text: >-
      I borrowed money from a friend and haven't paid it back yet. Now I feel
      ashamed.
    example_title: guilty 2
  - text: I'm starting to think that he's up to something.
    example_title: suspicious 2
  - text: We need to approach this matter with a sense of purpose
    example_title: serious 2

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:

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.

{'label': 'impatient', 'score': 0.924211859703064} I can't wait any longer