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- Run emotion model with 3 lines of code on single text example using Hugging Face's pipeline command:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  [![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)
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- Run emotion model on multiple examples and full datasets (e.g., .csv files):
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  [![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)
 
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+ ## Description
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+ This deep neural network classifies the emotions in English text data. The model was trained on diverse datasets and predicts 7 emotions:
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+ 1) anger
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+ 2) disgust
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+ 3) fear
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+ 4) joy
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+ 5) neutral
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+ 6) sadness
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+ 7) surprise
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+ ## Application
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+ a) Run emotion model with 3 lines of code on single text example using Hugging Face's pipeline command:
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  [![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)
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+ b) Run emotion model on multiple examples and full datasets (e.g., .csv files):
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  [![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)