File size: 1,212 Bytes
092a428 75b9a09 80a6c9d 75b9a09 04392f3 75b9a09 f7dc7cd c1f87b8 f7dc7cd c1f87b8 80a6c9d 93618c7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
---
widget:
- text: "Oh wow. Where is that from??"
- text: "This movie always makes me cry.."
---
## Description
With this model, you can classify emotions in English text data. The model was trained on diverse datasets and predicts 7 emotions:
1) anger
2) disgust
3) fear
4) joy
5) neutral
6) sadness
7) surprise
The model is a fine-tuned checkpoint of DistilRoBERTa-base.
## Application
a) Run emotion model with 3 lines of code on single text example using Hugging Face's pipeline command on Google Colab:
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/j-hartmann/emotion-english-distilroberta-base/blob/main/simple_emotion_pipeline.ipynb)
b) Run emotion model on multiple examples and full datasets (e.g., .csv files) on Google Colab:
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/j-hartmann/emotion-english-distilroberta-base/blob/main/emotion_prediction_example.ipynb)
## Contact
Please reach out to jochen.hartmann@uni-hamburg.de if you have any questions or feedback.
Thanks to S.D. and chrsiebert for their support in making this model available. |